• A learning-based model that enables deformation-aware 3D sketching without requiring reconstruction-and-simulation. • A synthetic dataset of 40K sketch-deformation pairs spanning 3D sketches of architectural thin-shell structures and their corresponding deformation fields derived from Finite Element Analysis (FEA). • A dual-head physics-informed neural network that decouples deformation field estimation into predicting unit-length displacement vectors and scalar displacement magnitudes. • Physics-guided regularization terms incorporating stretching and bending as the two modes of deformation.

Abstract Although variable‐rate compressed image formats such as JPEG are widely used to efficiently encode images, they have not found their way into real‐time rendering due to special requirements such as random access to individual texels. In this paper, we investigate the feasibility of variable‐rate texture compression on modern GPUs using the JPEG format, and how it compares to the GPU‐friendly fixed‐rate compression approaches BC1 and ASTC. Using a deferred rendering pipeline, we are able to identify the subset of blocks that are needed for a given frame, decode these, and colorize the framebuffer's pixels. Despite the additional ∼0.17 bit per pixel that we require for our approach, JPEG maintains significantly better quality and compression rates compared to BC1, and depending on the type of image, outperforms or competes with ASTC. The JPEG rendering pipeline increases rendering duration by less than 0.3 ms on an NVIDIA RTX 4090, demonstrating that sophisticated variable‐rate compression schemes are feasible on modern GPUs, even in VR. Source code and data sets are available at: https://github.com/elias1518693/jpeg_textures

Abstract This paper presents a CUDA‐based software rasterizer capable of rendering up to a billion unique triangles, or up to 4 billion instanced triangles, in real time at 60 fps on an RTX 5090. By specifically targeting dense, opaque meshes, our approach is able to outperform the native GPU rasterization pipeline in these scenarios. The resulting performance enables rapid loading and visualization of massive triangle datasets without requiring precomputed spatial acceleration or level‐of‐detail structures, and supports applications such as efficient editing of large‐scale geometry. While the method is primarily designed for dense meshes that generate pixel‐sized triangles, we additionally introduce a three‐stage pipeline to handle larger primitives. The source code is available at: https://github.com/m-schuetz/CuRast

Abstract Achieving realistic rendering of 3D scenes in real time using path tracing is challenging due to the high sample count required, with ray tracing as the bottleneck. Focusing on voxels as a geometry representation offers significant opportunities for optimizations, especially for tracing the rays, but also for computing the samples. We propose a novel multilayered spatial structure augmented with in‐cell axis‐aligned distance fields (AADF) operating as caches. Our nested cell structure already accelerates ray tracing 3‐5x compared to the state‐of‐the‐art dense spatial structures, such as variants of directed acyclic graphs (DAG). Using the AADFs (constructed while rendering) inside the cells, we can double the ray throughput again (total 10x). As an application, exploiting nested AADFs (NAADFs) also allows us to double the speed of global illumination computations while significantly reducing artifacts from camera motion, such as flickering, blurring, ghosting, and aliasing, all of which are especially important in voxel worlds with sharp edges. We achieve this by adapting temporal antialiasing (TAA) to retain the last 32 frames rather than a single history buffer to create the final antialiased image, since the discretized voxel structure requires much less memory to store the quantized positions and normals of ray bounces. The sample accumulation for global illumination is optimized by compressing and separating lit/unlit samples, and we apply 8x8 window spatial resampling based on a reservoir‐based spatiotemporal importance resampling (ReSTIR) method. Our proposed NAADFs support editing with quick updates to the acceleration in the background, overlays of non‐aligned dynamic geometry, and can be easily extended to support transform‐aware compression or to represent huge real‐world scans. Retaining many past frames rather than just combining them opens up new opportunities to remove spatial and temporal artifacts in path tracing for global illumination.

Parametric functions are an extremely efficient representation for 3D geometry, capable of compactly modelling highly complex objects. Once specified, parametric 3D objects allow for visualization at arbitrary levels of detail (LOD), at no additional memory cost, limited only by the amount of evaluated samples. However, mapping the sample evaluation to the hardware rendering pipelines of modern graphics processing units (GPUs) is not trivial. In this article, we propose a general method for efficient rendering of parametrically-defined 3D objects on modern hardware architectures. Our method adaptively analyzes, allocates and evaluates parametric function samples to produce high-quality renderings. Geometric precision can be modulated from few pixels down to sub-pixel level, enabling real-time frame rates of several 100 frames per second (FPS) for various parametric functions. We propose a dedicated LOD stage, which outputs patches of similar geometric detail to a subsequent rendering stage that uses either a hardware tessellation-based approach or performs point-based software rasterization. Our method requires neither preprocessing nor caching, and the proposed LOD mechanism is fast enough to run each frame. Hence, our approach also lends itself to animated parametric objects. We demonstrate the benefits of our method over a state-of-the-art spherical harmonics (SH) glyph rendering method and over classical LOD approaches, while showing its flexibility on a range of other demanding shapes.

Denoising is an important post-processing step in physically based Monte Carlo (MC) rendering. While neural networks are widely used in practice, statistical analysis has recently become a viable alternative for denoising. In this paper, we present a general framework for statistics-based error reduction of both estimated radiance and variance. Specifically, we introduce a novel denoising approach for variance estimates, which can either improve variance-aware adaptive sampling or provide additional input for image denoising in a cascaded manner. Furthermore, we present multi-transform denoising: a general and efficient correction scheme for non-normal distributions, which typically occur in MC rendering. All these contributions combine to a robust denoising pipeline that does not require any pretraining and can run efficiently on current GPU hardware. Our results show distinct advantages over previous denoising methods, especially in the range of a few hundred samples per pixel, which is of high practical relevance. Finally, we demonstrate good convergence behavior as the number of samples increases, providing predictable results with low bias that are free of hallucinated neural artifacts. In summary, our statistics-based algorithms for adaptive sampling and denoising deliver fast, consistent, low-bias variance and radiance estimates.

Recent advances in 3D generative models have shown promising results but often fall short in capturing the complexity of architectural geometries and topologies. To tackle this, we present ArchComplete, a two-stage voxel-based 3D generative pipeline consisting of a vector-quantized model, whose composition is modeled with an autoregressive transformer for generating coarse shapes, followed by a set of multiscale diffusion models for augmenting with fine geometric details. Key to our pipeline is (i) learning a contextually rich codebook of local patch embeddings, optimized alongside a 2.5D perceptual loss that captures global spatial correspondence of projections onto three axis-aligned orthogonal planes, and (ii) redefining upsampling as a set of multiscale conditional diffusion models learning over a hierarchy of coarse-to-fine local volumetric patches, with a guided denoising process using 3D Gaussian windows that smooths noise estimates across overlapping patches during inference. Trained on our introduced dataset of 3D house models, ArchComplete autoregressively generates models at the resolution of 6 4 3 and progressively refines them up to 51 2 3 , with voxel sizes as small as ≈ 9 cm . ArchComplete solves a variety of tasks, including genetic interpolation and variation, unconditional synthesis, shape and plan-drawing completion, as well as geometric detailization, while achieving state-of-the-art performance.

Abstract Since its introduction, 3D Gaussian Splatting (3DGS) has become an important reference method for learning 3D representations of a captured scene, allowing real‐time novel‐view synthesis with high visual quality and fast training times. Neural Radiance Fields (NeRFs), which preceded 3DGS, are based on a principled ray‐marching approach for volumetric rendering. In contrast, while sharing a similar image formation model with NeRF, 3DGS uses a hybrid rendering solution that builds on the strengths of volume rendering and primitive rasterization. A crucial benefit of 3DGS is its performance, achieved through a set of approximations, in many cases with respect to volumetric rendering theory. A naturally arising question is whether replacing these approximations with more principled volumetric rendering solutions can improve the quality of 3DGS. In this paper, we present an in‐depth analysis of the various approximations and assumptions used by the original 3DGS solution. We demonstrate that, while more accurate volumetric rendering can help for low numbers of primitives, the power of efficient optimization and the large number of Gaussians allows 3DGS to outperform volumetric rendering despite its approximations.

Abstract The early phase of urban planning and architectural design has a great impact on the thermal loads and characteristics of constructed buildings. It is, therefore, important to efficiently simulate thermal effects early on and rectify possible problems. In this paper, we present an inverse simulation of radiative heat transport and a differentiable photon‐tracing approach. Our method utilizes GPU‐accelerated ray tracing to speed up both the forward and adjoint simulation. Moreover, we incorporate matrix compression to further increase the efficiency of our thermal solver and support larger scenes. In addition to our differentiable photon‐tracing approach, we introduce a novel approximate edge sampling scheme that re‐uses primary samples instead of relying on explicit edge samples or auxiliary rays to resolve visibility discontinuities. Our inverse simulation system enables designers to not only predict the temperature distribution, but also automatically optimize the design to improve thermal comfort and avoid problematic configurations. We showcase our approach using several examples in which we optimize the placement of buildings or their facade geometry. Our approach can be used to optimize arbitrary geometric parameterizations and supports steady‐state, as well as transient simulations.

Abstract We present Splatshop, a highly optimized toolbox for interactive editing (selection, deletion, painting, transformation, …) of 3D Gaussian Splatting models. Utilizing a comprehensive collection of heuristic approaches, we carefully balance between exact and fast rendering to enable precise editing without sacrificing real‐time performance. Our experiments confirm that Splatshop achieves these goals for scenes with up to 100 million primitives. We also show how our proposed pipeline can be extended for use with head‐mounted displays. As such, Splatshop is the first VR‐capable editor for large‐scale 3D Gaussian Splatting models and a step towards a “Photoshop for Gaussian Splatting.”

Visual Parameter Space Analysis (VPSA) enables domain scientists to explore input-output relationships of computational models. Existing VPSA applications often feature multi-view visualizations designed by visualization experts for a specific scenario, making it hard for domain scientists to adapt them to their problems without professional help. We present RSVP, the Rapid Suggestive Visualization Prototyping system encoding VPSA knowledge to enable domain scientists to prototype custom visualization dashboards tailored to their specific needs. The system implements a task-oriented, multi-view visualization recommendation strategy over a visualization design space optimized for VPSA to guide users in meeting their analytical demands. We derived the VPSA knowledge implemented in the system by conducting an extensive meta design study over the body of work on VPSA. We show how this process can be used to perform a data and task abstraction, extract a common visualization design space, and derive a task-oriented VisRec strategy. User studies indicate that the system is user-friendly and can uncover novel insights.

International audience

Abstract 3D surface reconstruction from point clouds is a key step in areas such as content creation, archaeology, digital cultural heritage and engineering. Current approaches either try to optimize a non‐data‐driven surface representation to fit the points, or learn a data‐driven prior over the distribution of commonly occurring surfaces and how they correlate with potentially noisy point clouds. Data‐driven methods enable robust handling of noise and typically either focus on a global or a local prior, which trade‐off between robustness to noise on the global end and surface detail preservation on the local end. We propose PPSurf as a method that combines a global prior based on point convolutions and a local prior based on processing local point cloud patches. We show that this approach is robust to noise while recovering surface details more accurately than the current state‐of‐the‐art. Our source code, pre‐trained model and dataset are available at https://github.com/cg‐tuwien/ppsurf .

Abstract Reconstructing 2D curves from sample points has long been a critical challenge in computer graphics, finding essential applications in vector graphics. The design and editing of curves on surfaces has only recently begun to receive attention, primarily relying on human assistance, and where not, limited by very strict sampling conditions. In this work, we formally improve on the state‐of‐the‐art requirements and introduce an innovative algorithm capable of reconstructing closed curves directly on surfaces from a given sparse set of sample points. We extend and adapt a state‐of‐the‐art planar curve reconstruction method to the realm of surfaces while dealing with the challenges arising from working on non‐Euclidean domains. We demonstrate the robustness of our method by reconstructing multiple curves on various surface meshes. We explore novel potential applications of our approach, allowing for automated reconstruction of curves on Riemannian manifolds.

Abstract We present Strokes2Surface, an offline geometry reconstruction pipeline that recovers well‐connected curve networks from imprecise 4D sketches to bridge concept design and digital modeling stages in architectural design. The input to our pipeline consists of 3D strokes' polyline vertices and their timestamps as the 4th dimension, along with additional metadata recorded throughout sketching. Inspired by architectural sketching practices, our pipeline combines a classifier and two clustering models to achieve its goal. First, with a set of extracted hand‐engineered features from the sketch, the classifier recognizes the type of individual strokes between those depicting boundaries (Shape strokes) and those depicting enclosed areas (Scribble strokes). Next, the two clustering models parse strokes of each type into distinct groups, each representing an individual edge or face of the intended architectural object. Curve networks are then formed through topology recovery of consolidated Shape clusters and surfaced using Scribble clusters guiding the cycle discovery. Our evaluation is threefold: We confirm the usability of the Strokes2Surface pipeline in architectural design use cases via a user study, we validate our choice of features via statistical analysis and ablation studies on our collected dataset, and we compare our outputs against a range of reconstructions computed using alternative methods.

Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering inevitably limit the size of the captured scenes that can be represented with good visual quality. We introduce a hierarchy of 3D Gaussians that preserves visual quality for very large scenes, while offering an efficient Level-of-Detail (LOD) solution for efficient rendering of distant content with effective level selection and smooth transitions between levels. We introduce a divide-and-conquer approach that allows us to train very large scenes in independent chunks. We consolidate the chunks into a hierarchy that can be optimized to further improve visual quality of Gaussians merged into intermediate nodes. Very large captures typically have sparse coverage of the scene, presenting many challenges to the original 3D Gaussian splatting training method; we adapt and regularize training to account for these issues. We present a complete solution, that enables real-time rendering of very large scenes and can adapt to available resources thanks to our LOD method. We show results for captured scenes with up to tens of thousands of images with a simple and affordable rig, covering trajectories of up to several kilometers and lasting up to one hour.

Differentiable rendering methods promise the ability to optimize various parameters of three-dimensional (3D) scenes to achieve a desired result. However, lighting design has so far received little attention in this field. In this article, we introduce a method that enables continuous optimization of the arrangement of luminaires in a 3D scene via differentiable light tracing. Our experiments show two major issues when attempting to apply existing methods from differentiable path tracing to this problem: First, many rendering methods produce images, which restricts the ability of a designer to define lighting objectives to image space. Second, most previous methods are designed for scene geometry or material optimization and have not been extensively tested for the case of optimizing light sources. Currently available differentiable ray-tracing methods do not provide satisfactory performance, even on fairly basic test cases in our experience. In this article, we propose, to the best of our knowledge, a novel adjoint light tracing method that overcomes these challenges and enables gradient-based lighting design optimization in a view-independent (camera-free) way. Thus, we allow the user to paint illumination targets directly onto the 3D scene or use existing baked illumination data (e.g., light maps). Using modern ray-tracing hardware, we achieve interactive performance. We find light tracing advantageous over path tracing in this setting, as it naturally handles irregular geometry, resulting in less noise and improved optimization convergence. We compare our adjoint gradients to state-of-the-art image-based differentiable rendering methods. We also demonstrate that our gradient data works with various common optimization algorithms, providing good convergence behaviour. Qualitative comparisons with real-world scenes underline the practical applicability of our method.

State-of-the-art workflows within Architecture, Engineering, and Construction (AEC) are still caught in sequential planning processes. Digital design tools in this domain often lack proper communication between different stages of design and relevant domain knowledge. Furthermore, decisions made in the early stages of design, where sketching is used to initiate, develop, and communicate ideas, heavily impact later stages, resulting in the need for rapid feedback to the architectural designer so they can proceed with adequate knowledge about design implications. Accordingly, this paper presents research on a novel integrative design framework based on a recently developed 4D sketching interface, targeted for architectural design as a form-finding tool coupled with three modules: (1) a Geometric Modelling module, which utilises Points2Surf as a machine learning model for automatic surface mesh reconstruction from the point clouds produced by sketches, (2) a Material Modelling module, which predicts the mechanical properties of biocomposites based on multiscale micromechanics homogenisation techniques, and (3) a Structural Analysis module, which assesses the mechanical performance of the meshed structure on the basis of the predicted material properties using finite element simulations. The proposed framework is a step towards using material-informed design already in the early stages of design.

For over two decades, the OpenGL API provided users with the means for implementing versatile, feature-rich, and portable real-time graphics applications. Consequently, it has been widely adopted by practitioners and educators alike and is deeply ingrained in many curricula that teach real-time graphics for higher education. Over the years, the architecture of graphics processing units (GPUs) incrementally diverged from OpenGL’s conceptual design. The more recently introduced Vulkan API provides a more modern, fine-grained approach for interfacing with the GPU, which allows a high level of controllability and, thereby, deep insights into the inner workings of modern GPUs. This property makes the Vulkan API especially well suitable for teaching graphics programming in university education, where fundamental knowledge shall be conveyed. Hence, it stands to reason that educators who have their students’ best interests at heart should provide them with corresponding lecture material. However, Vulkan is notoriously verbose and rather challenging for first-time users, thus transitioning to this new API bears a considerable risk of failing to achieve expected teaching goals. In this paper, we document our experiences after teaching Vulkan in both introductory and advanced graphics courses side-by-side with conventional OpenGL. A collection of surveys enables us to draw conclusions about perceived workload, difficulty, and students’ acceptance of either approach. In doing so, we identify suitable conditions and recommendations for teaching Vulkan to both undergraduate and graduate students.

Architectural design and urban planning are complex design tasks. Predicting the thermal impact of design choices at interactive rates enhances the ability of designers to improve energy efficiency and avoid problematic heat islands while maintaining design quality. We show how to use and adapt methods from computer graphics to efficiently simulate heat transfer via thermal radiation, thereby improving user guidance in the early design phase of large-scale construction projects and helping to increase energy efficiency and outdoor comfort. Our method combines a hardware-accelerated photon tracing approach with a carefully selected finite element discretization, inspired by precomputed radiance transfer. This combination allows us to precompute a radiative transport operator, which we then use to rapidly solve either steady-state or transient heat transport throughout the entire scene. Our formulation integrates time-dependent solar irradiation data without requiring changes in the transport operator, allowing us to quickly analyze many different scenarios such as common weather patterns, monthly or yearly averages, or transient simulations spanning multiple days or weeks. We show how our approach can be used for interactive design workflows such as city planning via fast feedback in the early design phase.

Abstract About: We introduce a GPU‐accelerated LOD construction process that creates a hybrid voxel‐point‐based variation of the widely used layered point cloud (LPC) structure for LOD rendering and streaming. The massive performance improvements provided by the GPU allow us to improve the quality of lower LODs via color filtering while still increasing construction speed compared to the non‐filtered, CPU‐based state of the art. Background: LOD structures are required to render hundreds of millions to trillions of points, but constructing them takes time. Results: LOD structures suitable for rendering and streaming are constructed at rates of about 1 billion points per second (with color filtering) to 4 billion points per second (sample‐picking/random sampling, state of the art) on an RTX 3090 – an improvement of a factor of 80 to 400 times over the CPU‐based state of the art (12 million points per second). Due to being in‐core, model sizes are limited to about 500 million points per 24GB memory. Discussion: Our method currently focuses on maximizing in‐core construction speed on the GPU. Issues such as out‐of‐core construction of arbitrarily large data sets are not addressed, but we expect it to be suitable as a component of bottom‐up out‐of‐core LOD construction schemes.

Abstract Determining connectivity between points and reconstructing their shape boundaries are long‐standing problems in computer graphics. One possible approach to solve these problems is to use a proximity graph. We propose a new proximity graph computed by intersecting the to‐date rarely used proximity‐based graph called spheres‐of‐influence graph (SIG) with the Delaunay triangulation (DT). We prove that the resulting graph, which we name SIGDT, contains the piece‐wise linear reconstruction for a set of unstructured points in the plane for a sampling condition superseding current bounds and capturing well practical point sets' properties. As an application, we apply a dual of boundary adjustment steps from the Connect2D algorithm to remove the redundant edges. We show that the resulting algorithm SIG‐Connect2D yields the best reconstruction accuracy compared to state‐of‐the‐art algorithms from a recent comprehensive benchmark, and the method offers the potential for further improvements, e.g., for surface reconstruction.

Abstract In this paper, we present several compute‐based point cloud rendering approaches that outperform the hardware pipeline by up to an order of magnitude and achieve significantly better frame times than previous compute‐based methods. Beyond basic closest‐point rendering, we also introduce a fast, high‐quality variant to reduce aliasing. We present and evaluate several variants of our proposed methods with different flavors of optimization, in order to ensure their applicability and achieve optimal performance on a range of platforms and architectures with varying support for novel GPU hardware features. During our experiments, the observed peak performance was reached rendering 796 million points (12.7GB) at rates of 62 to 64 frames per second (50 billion points per second, 802GB/s) on an RTX 3090 without the use of level‐of‐detail structures. We further introduce an optimized vertex order for point clouds to boost the efficiency of GL_POINTS by a factor of 5× in cases where hardware rendering is compulsory. We compare different orderings and show that Morton sorted buffers are faster for some viewpoints, while shuffled vertex buffers are faster in others. In contrast, combining both approaches by first sorting according to Morton‐code and shuffling the resulting sequence in batches of 128 points leads to a vertex buffer layout with high rendering performance and low sensitivity to viewpoint changes.

Abstract Following recent advances in GPU hardware development and newly introduced rendering pipeline extensions, the segmentation of input geometry into small geometry clusters—so‐called meshlets—has emerged as an important practice for efficient rendering of complex 3D models. Meshlets can be processed efficiently using mesh shaders on modern graphics processing units, in order to achieve streamlined geometry processing in just two tightly coupled shader stages that allow for dynamic workload manipulation in‐between. The additional granularity layer between entire models and individual triangles enables new opportunities for fine‐grained visibility culling methods. However, in contrast to static models, view frustum and backface culling on a per‐meshlet basis for skinned, animated models are difficult to achieve while respecting the conservative spatio‐temporal bounds that are required for robust rendering results. In this paper, we describe a solution for computing and exploiting relevant conservative bounds for culling meshlets of models that are animated using linear blend skinning. By enabling visibility culling for animated meshlets, our approach can help to improve rendering performance and alleviate bottlenecks in the notoriously performance‐ and memory‐intensive skeletal animation pipelines of modern real‐time graphics applications.

Abstract Large-scale unstructured point cloud scenes can be quickly visualized without prior reconstruction by utilizing levels-of-detail structures to load an appropriate subset from out-of-core storage for rendering the current view. However, as soon as we need structures within the point cloud, e.g., for interactions between objects, the construction of state-of-the-art data structures requires O(NlogN) time for N points, which is not feasible in real time for millions of points that are possibly updated in each frame. Therefore, we propose to use a surface representation structure which trades off the (here negligible) disadvantage of single-frame use for both output-dominated and near-linear construction time in practice, exploiting the inherent 2D property of sampled surfaces in 3D. This structure tightly encompasses the assumed surface of unstructured points in a set of bounding depth intervals for each cell of a discrete 2D grid. The sorted depth samples in the structure permit fast surface queries, and on top of that an occlusion graph for the scene comes almost for free. This graph enables novel real-time user operations such as revealing partially occluded objects, or scrolling through layers of occluding objects, e.g., walls in a building. As an example application we showcase a 3D scene exploration framework that enables fast, more sophisticated interactions with point clouds rendered in real time.

Light-field cameras are becoming more popular in the consumer market. Their data redundancy allows, in theory, to accurately refocus images after acquisition and to predict the depth of each point visible from the camera. Combined, these two features allow for the generation of full-focus images, which is impossible in traditional cameras. Multiple methods for depth prediction from light fields (or stereo) have been proposed over the years. A large subset of these methods relies on cost-volume estimates - 3D objects where each layer represents a heuristic of whether each point in the image is at a certain distance from the camera. Generally, this volume is used to regress a depth map, which is then refined for better results. In this paper, we argue that refining the cost volumes is superior to refining the depth maps in order to further increase the accuracy of depth predictions. We propose a set of cost-volume refinement algorithms and show their effectiveness.

For our society to be more inclusive and accessible, the more than 2.2 billion people worldwide with limited vision should be considered more frequently in design decisions, such as architectural planning. To help architects in evaluating their designs and give medical personnel some insight on how patients experience cataracts, we worked with ophthalmologists to develop the first medically-informed, pilot-studied simulation of cataracts in eye-tracked augmented reality (AR). To test our methodology and simulation, we conducted a pilot study with cataract patients between surgeries of their two cataract-affected eyes. Participants compared the vision of their corrected eye, viewing through simulated cataracts, to that of their still affected eye, viewing an unmodified AR view. In addition, we conducted remote experiments via video call, live adjusting our simulation and comparing it to related work, with participants who had cataract surgery a few months before. We present our findings and insights from these experiments and outline avenues for future work.

Abstract Research in rendering large point clouds traditionally focused on the generation and use of hierarchical acceleration structures that allow systems to load and render the smallest fraction of the data with the largest impact on the output. The generation of these structures is slow and time consuming, however, and therefore ill‐suited for tasks such as quickly looking at scan data stored in widely used unstructured file formats, or to immediately display the results of point‐cloud processing tasks. We propose a progressive method that is capable of rendering any point cloud that fits in GPU memory in real time, without the need to generate hierarchical acceleration structures in advance. Our method supports data sets with a large amount of attributes per point, achieves a load performance of up to 100 million points per second, displays already loaded data in real time while remaining data is still being loaded, and is capable of rendering up to one billion points using an on‐the‐fly generated shuffled vertex buffer as its data structure, instead of slow‐to‐generate hierarchical structures. Shuffling is done during loading in order to allow efficiently filling holes with random subsets, which leads to a higher quality convergence behavior.

Abstract We propose an efficient out‐of‐core octree generation method for arbitrarily large point clouds. It utilizes a hierarchical counting sort to quickly split the point cloud into small chunks, which are then processed in parallel. Levels of detail are generated by subsampling the full data set bottom up using one of multiple exchangeable sampling strategies. We introduce a fast hierarchical approximate blue‐noise strategy and compare it to a uniform random sampling strategy. The throughput, including out‐of‐core access to disk, generating the octree, and writing the final result to disk, is about an order of magnitude faster than the state of the art, and reaches up to around 6 million points per second for the blue‐noise approach and up to around 9 million points per second for the uniform random approach on modern SSDs.

Abstract Creating photorealistic materials for light transport algorithms requires carefully fine‐tuning a set of material properties to achieve a desired artistic effect. This is typically a lengthy process that involves a trained artist with specialized knowledge. In this work, we present a technique that aims to empower novice and intermediate‐level users to synthesize high‐quality photorealistic materials by only requiring basic image processing knowledge. In the proposed workflow, the user starts with an input image and applies a few intuitive transforms (e.g., colorization, image inpainting) within a 2D image editor of their choice, and in the next step, our technique produces a photorealistic result that approximates this target image. Our method combines the advantages of a neural network‐augmented optimizer and an encoder neural network to produce high‐quality output results within 30 seconds. We also demonstrate that it is resilient against poorly‐edited target images and propose a simple extension to predict image sequences with a strict time budget of 1–2 seconds per image.

The perception of light is inherently different inside a virtual reality (VR) or augmented reality (AR) simulation when compared to the real world. Conventional head-worn displays (HWDs) are not able to display the same high dynamic range of brightness and color as the human eye can perceive in the real world. To mimic the perception of real-world scenes in virtual scenes, it is crucial to reproduce the effects of incident light on the human visual system. In order to advance virtual simulations towards perceptual realism, we present an eye-tracked VR/AR simulation comprising effects for gaze-dependent temporal eye adaption, perceptual glare, visual acuity reduction, and scotopic color vision. Our simulation is based on medical expert knowledge and medical studies of the healthy human eye. We conducted the first user study comparing the perception of light in a real-world low-light scene to a VR simulation. Our results show that the proposed combination of simulated visual effects is well received by users and also indicate that an individual adaptation is necessary, because perception of light is highly subjective.

Global Illumination is affected by the slightest change in a 3D scene, requiring a complete reevaluation of the distributed light. In cases where real-time algorithms are not applicable due to high demands on the achievable accuracy, this recomputation from scratch results in artifacts like flickering or noise, disturbing the visual appearance and negatively affecting interactive lighting design workflows.

In this work, we propose an interaction-driven approach streamlined to support and improve a wide range of real-time 2D interaction metaphors for arbitrarily large pointclouds based on detected primitive shapes. Rather than performing shape detection as a costly pre-processing step on the entire point cloud at once, a user-controlled interaction determines the region that is to be segmented next. By keeping the size of the region and the number of points small, the algorithm produces meaningful results and therefore feedback on the local geometry within a fraction of a second. We can apply these finding for improved picking and selection metaphors in large point clouds, and propose further novel shape-assisted interactions that utilize this local semantic information to improve the user's workflow.

Vision impairments, such as cataracts, affect the way many people interact with their environment, yet are rarely considered by architects and lighting designers because of a lack of design tools. To address this, we present a method to simulate vision impairments, in particular cataracts, graphically in virtual reality (VR), using eye tracking for gaze-dependent effects. We also conduct a VR user study to investigate the effects of lighting on visual perception for users with cataracts. In contrast to existing approaches, which mostly provide only simplified simulations and are primarily targeted at educational or demonstrative purposes, we account for the user's vision and the hardware constraints of the VR headset. This makes it possible to calibrate our cataract simulation to the same level of degraded vision for all participants. Our study results show that we are able to calibrate the vision of all our participants to a similar level of impairment, that maximum recognition distances for escape route signs with simulated cataracts are significantly smaller than without, and that luminaires visible in the field of view are perceived as especially disturbing due to the glare effects they create. In addition, the results show that our realistic simulation increases the understanding of how people with cataracts see and could therefore also be informative for health care personnel or relatives of cataract patients.

Real-time rendering of large point clouds requires acceleration structures that reduce the number of points drawn on screen. State-of-the art algorithms group and render points in hierarchically organized chunks with varying extent and density, which results in sudden changes of density from one level of detail to another, as well as noticeable popping artifacts when additional chunks are blended in or out. These popping artifacts are especially noticeable at lower levels of detail, and consequently in virtual reality, where high performance requirements impose a reduction in detail. We propose a continuous level-of-detail method that exhibits gradual rather than sudden changes in density. Our method continuously recreates a down-sampled vertex buffer from the full point cloud, based on camera orientation, position, and distance to the camera, in a point-wise rather than chunk-wise fashion and at speeds up to 17 million points per millisecond. As a result, additional details are blended in or out in a less noticeable and significantly less irritating manner as compared to the state of the art. The improved acceptance of our method was successfully evaluated in a user study.

Live coding in virtual reality allows users to create and modify their surroundings through code without the need to leave the virtual reality environment. Previous work focuses on modifying the scene. We propose an application that allows developers to modify virtually everything at runtime, including the scene but also the render engine, shader code and input handling, using standard desktop IDEs through a desktop mirror.

Abstract This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal‐time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two‐fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per‐pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per‐pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.

Abstract In this paper, we present a real‐time technique to visualize large‐scale adaptive height fields with C ‐continuous surface reconstruction. Grid‐based shallow water simulation is an indispensable tool for interactive flood management applications. Height fields defined on adaptive grids are often the only viable option to store and process the massive simulation data. Their visualization requires the reconstruction of a continuous surface from the spatially discrete simulation data. For regular grids, fast linear and cubic interpolation are commonly used for surface reconstruction. For adaptive grids, however, there exists no higher‐order interpolation technique fast enough for interactive applications. Our proposed technique bridges the gap between fast linear and expensive higher‐order interpolation for adaptive surface reconstruction. During reconstruction, no matter if regular or adaptive, discretization and interpolation artifacts can occur, which domain experts consider misleading and unaesthetic. We take into account boundary conditions to eliminate these artifacts, which include water climbing uphill, diving towards walls, and leaking through thin objects. We apply realistic water shading with visual cues for depth perception and add waves and foam synthesized from the simulation data to emphasize flow directions. The versatility and performance of our technique are demonstrated in various real‐world scenarios. A survey conducted with domain experts of different backgrounds and concerned citizens proves the usefulness and effectiveness of our technique.

Abstract We propose a parameter‐free method to recover manifold connectivity in unstructured 2D point clouds with high noise in terms of the local feature size. This enables us to capture the features which emerge out of the noise. To achieve this, we extend the reconstruction algorithm HNN‐Crust, which connects samples to two (noise‐free) neighbours and has been proven to output a manifold for a relaxed sampling condition. Applying this condition to noisy samples by projecting their k‐nearest neighbourhoods onto local circular fits leads to multiple candidate neighbour pairs and thus makes connecting them consistently an NP‐hard problem. To solve this efficiently, we design an algorithm that searches that solution space iteratively on different scales of k. It achieves linear time complexity in terms of point count plus quadratic time in the size of noise clusters. Our algorithm FitConnect extends HNN‐Crust seamlessly to connect both samples with and without noise, performs as local as the recovered features and can output multiple open or closed piecewise curves. Incidentally, our method simplifies the output geometry by eliminating all but a representative point from noisy clusters. Since local neighbourhood fits overlap consistently, the resulting connectivity represents an ordering of the samples along a manifold. This permits us to simply blend the local fits for denoising with the locally estimated noise extent. Aside from applications like reconstructing silhouettes of noisy sensed data, this lays important groundwork to improve surface reconstruction in 3D. Our open‐source algorithm is available online.

Probabilistic distribution models like Gaussian mixtures have shown great potential for improving both the quality and speed of several geometric operators. This is largely due to their ability to model large fuzzy data using only a reduced set of atomic distributions, allowing for large compression rates at minimal information loss. We introduce a new surface model that utilizes these qualities of Gaussian mixtures for the definition and control of a parametric smooth surface. Our approach is based on an enriched mesh data structure, which describes the probability distribution of spatial surface locations around each vertex via a Gaussian covariance matrix. By incorporating this additional covariance information, we show how to define a smooth surface via a nonlinear probabilistic subdivision operator based on products of Gaussians, which is able to capture rich details at fixed control mesh resolution. This entails new applications in surface reconstruction, modeling, and geometric compression.

Abstract This paper presents the latest advances and research in Computer Graphics education in a nutshell. It is concerned with topics that were presented at the Education Track of the Eurographics Conference held in Lisbon in 2016. We describe works corresponding to approaches to Computer Graphics education that are unconventional in some way and attempt to tackle unsolved problems and challenges regarding the role of arts in computer graphics education, the role of research‐oriented activities in undergraduate education and the interaction among different areas of Computer Graphics, as well as their application to courses or extra‐curricular activities. We present related works addressing these topics and report experiences, successes and issues in implementing the approaches.

We present a learning-based system for rapid mass-scale material synthesis that is useful for novice and expert users alike. The user preferences are learned via Gaussian Process Regression and can be easily sampled for new recommendations. Typically, each recommendation takes 40-60 seconds to render with global illumination, which makes this process impracticable for real-world workflows. Our neural network eliminates this bottleneck by providing high-quality image predictions in real time, after which it is possible to pick the desired materials from a gallery and assign them to a scene in an intuitive manner. Workflow timings against Disney's "principled" shader reveal that our system scales well with the number of sought materials, thus empowering even novice users to generate hundreds of high-quality material models without any expertise in material modeling. Similarly, expert users experience a significant decrease in the total modeling time when populating a scene with materials. Furthermore, our proposed solution also offers controllable recommendations and a novel latent space variant generation step to enable the real-time fine-tuning of materials without requiring any domain expertise.

We present a novel framework for visualizing routes on mobile devices. Our framework is suitable for helping users explore their environment. First, given a starting point and a maximum route length, the system retrieves nearby points of interest (POIs). Second, we automatically compute an attractive walking path through the environment trying to pass by as many highly ranked POIs as possible. Third, we automatically compute a route visualization that shows the current user position, POI locations via pins, and detail lenses for more information about the POIs. The visualization is an animation of an orthographic map view that follows the current user position. We propose an optimization based on a binary integer program (BIP) that models multiple requirements for an effective placement of detail lenses. We show that our path computation method outperforms recently proposed methods and we evaluate the overall impact of our framework in two user studies.

Finding similar points in globally or locally similar shapes has been studied extensively through the use of various point descriptors or shape-matching methods. However, little work exists on finding similar points in dissimilar shapes. In this paper, we present the results of a study where users were given two dissimilar two-dimensional shapes and asked to map a given point in the first shape to the point in the second shape they consider most similar. We find that user mappings in this study correlate strongly with simple geometric relationships between points and shapes. To predict the probability distribution of user mappings between any pair of simple two-dimensional shapes, two distinct statistical models are defined using these relationships. We perform a thorough validation of the accuracy of these predictions and compare our models qualitatively and quantitatively to well-known shape-matching methods. Using our predictive models, we propose an approach to map objects or procedural content between different shapes in different design scenarios.

In workplaces or publicly accessible buildings, escape routes are signposted according to official norms or international standards that specify distances, angles and areas of interest for the positioning of escape-route signs. In homes for the elderly, in which the residents commonly have degraded mobility and suffer from vision impairments caused by age or eye diseases, the specifications of current norms and standards may be insufficient. Quantifying the effect of symptoms of vision impairments like reduced visual acuity on recognition distances is challenging, as it is cumbersome to find a large number of user study participants who suffer from exactly the same form of vision impairments. Hence, we propose a new methodology for such user studies: By conducting a user study in virtual reality (VR), we are able to use participants with normal or corrected sight and simulate vision impairments graphically. The use of standardized medical eyesight tests in VR allows us to calibrate the visual acuity of all our participants to the same level, taking their respective visual acuity into account. Since we primarily focus on homes for the elderly, we accounted for their often limited mobility by implementing a wheelchair simulation for our VR application.

Grass plays an important role in most natural environments. Most interactive applications use image-based techniques to approximate fields of grass due to the high geometrical complexity, leading to visual artifacts. In this paper, we propose a grass-rendering technique that is capable of drawing each blade of grass as geometrical object in real time. Accurate culling methods together with an adaptable rendering pipeline ensure that only the blades of grass that are important for the visual appearance of the field of grass are rendered. In addition, we introduce a physical model that is evaluated for each blade of grass. This enables that a blade of grass can react to its environment by calculating the influence of gravity, wind and collisions. A major advantage of our approach is that it can render fields of grass of arbitrary shape and spatial alignment. Thus, in contrast to previous work, the blades of grass can be placed on any 3D model, which is not required to be a flat surface or a height map.

Capturing urban scenes using photogrammetric methods has become an interesting alternative to laser scanning in the past years. For the reconstruction of CAD-ready 3D models, two main types of interactive approaches have become prevalent: One uses the generated 3D point clouds to reconstruct polygonal surfaces, while the other focuses on 2D interaction in the photos to define edges and faces.

Abstract Traditionally, building floor plans are designed by architects with their usability, functionality and architectural aesthetics in mind; however, the structural properties of the distribution of load‐bearing walls and columns are usually not taken into account at this stage. In this paper, we propose a novel approach for the design of architectural floor plans by integrating structural layout analysis directly into the planning process. In order to achieve this, we introduce a planning tool which interactively enforces checks for structural stability of the current design, and which on demand proposes how to stabilize it if necessary. Technically, our solution contains an interactive architectural modelling framework as well as a constrained optimization module where both are based on respective architectural rules. Using our tool, an architect can predict already in a very early planning stage whose designs are structurally sound such that later changes due to stability reasons can be prevented. We compare manually computed solutions with optimal results of our proposed automated design process in order to show how much our proposed system can help architects to improve the process of laying out structural models optimally.

Abstract We consider the problem of sampling points from a collection of smooth curves in the plane, such that the Crust family of proximity‐based reconstruction algorithms can rebuild the curves. Reconstruction requires a dense sampling of local features, i.e., parts of the curve that are close in Euclidean distance but far apart geodesically. We show that ε < 0.47‐sampling is sufficient for our proposed HNN‐Crust variant, improving upon the state‐of‐the‐art requirement of ε < ‐sampling. Thus we may reconstruct curves with many fewer samples. We also present a new sampling scheme that reduces the required density even further than ε < 0.47‐sampling. We achieve this by better controlling the spacing between geodesically consecutive points. Our novel sampling condition is based on the reach, the minimum local feature size along intervals between samples. This is mathematically closer to the reconstruction density requirements, particularly near sharp‐angled features. We prove lower and upper bounds on reach ρ‐sampling density in terms of lfs ε‐sampling and demonstrate that we typically reduce the required number of samples for reconstruction by more than half.

In this paper we present a novel method for non-linear shape optimization of 3d objects given by their surface representation. Our method takes advantage of the fact that various shape properties of interest give rise to underdetermined design spaces implying the existence of many good solutions. Our algorithm exploits this by performing iterative projections of the problem to local subspaces where it can be solved much more efficiently using standard numerical routines. We demonstrate how this approach can be utilized for various shape optimization tasks using different shape parameterizations. In particular, we show how to efficiently optimize natural frequencies, mass properties, as well as the structural yield strength of a solid body. Our method is flexible, easy to implement, and very fast.

With the enormous advances of the acquisition technology over the last years, fast processing and high-quality visualization of large point clouds have gained increasing attention. Commonly, a mesh surface is reconstructed from the point cloud and a high-resolution texture is generated over the mesh from the images taken at the site to represent surface materials. However, this global reconstruction and texturing approach becomes impractical with increasing data sizes. Recently, due to its potential for scalability and extensibility, a method for texturing a set of depth maps in a preprocessing and stitching them at runtime has been proposed to represent large scenes. However, the rendering performance of this method is strongly dependent on the number of depth maps and their resolution. Moreover, for the proposed scene representation, every single depth map has to be textured by the images, which in practice heavily increases processing costs. In this paper, we present a novel method to break these dependencies by introducing an efficient raytracing of multiple depth maps. In a preprocessing phase, we first generate high-resolution textured depth maps by rendering the input points from image cameras and then perform a graph-cut based optimization to assign a small subset of these points to the images. At runtime, we use the resulting point-to-image assignments (1) to identify for each view ray which depth map contains the closest ray-surface intersection and (2) to efficiently compute this intersection point. The resulting algorithm accelerates both the texturing and the rendering of the depth maps by an order of magnitude.

Pixel art was frequently employed in games of the 90s and earlier. On today's large and high-resolution displays, pixel art looks blocky. Recently, an algorithm was introduced [Kopf and Lischinski 2011] to create a smooth, resolution-independent vector representation from pixel art. However, the algorithm is far too slow for interactive use, for example in a game. This poster presents an efficient implementation of the algorithm on the GPU, so that it runs at real-time rates and can be incorporated into current game emulators.

Recent advances in graphics hardware have made it a desirable goal to implement the Reyes algorithm on current graphics cards. One key component in this algorithm is the bound-and-split phase, where surface patches are recursively split until they are smaller than a given screen-space bound. While this operation has been successfully parallelized for execution on the GPU using a breadth-first traversal, the resulting implementations are limited by their unpredictable worst-case memory consumption and high global memory bandwidth utilization. In this paper, we propose an alternate strategy that allows limiting the amount of necessary memory by controlling the number of assigned worker threads. The result is an implementation that scales to the performance of the breadth-first approach while offering three advantages: significantly decreased memory usage, a smooth and predictable tradeoff between memory usage and performance, and increased locality for surface processing. This allows us to render scenes that would require too much memory to be processed by the breadth-first method.

Abstract In this paper, we present a method for non‐rigid, partial shape matching in vector graphics. Given a user‐specified query region in a 2D shape, similar regions are found, even if they are non‐linearly distorted. Furthermore, a non‐linear mapping is established between the query regions and these matches, which allows the automatic transfer of editing operations such as texturing. This is achieved by a two‐step approach. First, pointwise correspondences between the query region and the whole shape are established. The transformation parameters of these correspondences are registered in an appropriate transformation space. For transformations between similar regions, these parameters form surfaces in transformation space, which are extracted in the second step of our method. The extracted regions may be related to the query region by a non‐rigid transform, enabling non‐rigid shape matching.

Abstract We present a novel procedural framework for interactively modeling building façades. Common procedural approaches, such as shape grammars, assume that building façades are organized in a tree structure, while in practice this is often not the case. Consequently, the complexity of their layout description becomes unmanageable for interactive editing. In contrast, we obtain a façade by composing multiple overlapping layers, where each layer contains a single rectilinear grid of façade elements described by two simple generator patterns. This way, the design process becomes more intuitive and the editing effort for complex layouts is significantly reduced. To achieve this, we present a method for the automated merging of different layers in the form of a mixed discrete and continuous optimization problem. Finally, we provide several modeling examples and a comparison to shape grammars in order to highlight the advantages of our method when designing realistic building façades.

In this paper, we propose two real‐time models for simulating subsurface scattering for a large variety of translucent materials, which need under 0.5 ms per frame to execute. This makes them a practical option for real‐time production scenarios. Current state‐of‐the‐art, real‐time approaches simulate subsurface light transport by approximating the radially symmetric non‐separable diffusion kernel with a sum of separable Gaussians, which requires multiple (up to 12) 1D convolutions. In this work we relax the requirement of radial symmetry to approximate a 2D diffuse reflectance profile by a single separable kernel. We first show that low‐rank approximations based on matrix factorization outperform previous approaches, but they still need several passes to get good results. To solve this, we present two different separable models: the first one yields a high‐quality diffusion simulation, while the second one offers an attractive trade‐off between physical accuracy and artistic control. Both allow rendering of subsurface scattering using only two 1D convolutions, reducing both execution time and memory consumption, while delivering results comparable to techniques with higher cost. Using our importance‐sampling and jittering strategies, only seven samples per pixel are required. Our methods can be implemented as simple post‐processing steps without intrusive changes to existing rendering pipelines.

Abstract We propose a new technique for in‐core and out‐of‐core GPU ray tracing using a generalization of hierarchical occlusion culling in the style of the CHC++ method. Our method exploits the rasterization pipeline and hardware occlusion queries in order to create coherent batches of work for localized shader‐based ray tracing kernels. By combining hierarchies in both ray space and object space, the method is able to share intermediate traversal results among multiple rays. We exploit temporal coherence among similar ray sets between frames and also within the given frame. A suitable management of the current visibility state makes it possible to benefit from occlusion culling for less coherent ray types like diffuse reflections. Since large scenes are still a challenge for modern GPU ray tracers, our method is most useful for scenes with medium to high complexity, especially since our method inherently supports ray tracing highly complex scenes that do not fit in GPU memory. For in‐core scenes our method is comparable to CUDA ray tracing and performs up to5.94× better than pure shader‐based ray tracing.

Given the 2-manifold surface of a 3d object, we propose a novel method for the computation of an offset surface with varying thickness such that the solid volume between the surface and its offset satisfies a set of prescribed constraints and at the same time minimizes a given objective functional. Since the constraints as well as the objective functional can easily be adjusted to specific application requirements, our method provides a flexible and powerful tool for shape optimization. We use manifold harmonics to derive a reduced-order formulation of the optimization problem, which guarantees a smooth offset surface and speeds up the computation independently from the input mesh resolution without affecting the quality of the result. The constrained optimization problem can be solved in a numerically robust manner with commodity solvers. Furthermore, the method allows simultaneously optimizing an inner and an outer offset in order to increase the degrees of freedom. We demonstrate our method in a number of examples where we control the physical mass properties of rigid objects for the purpose of 3d printing.

We present a method to learn and propagate shape placements in 2D polygonal scenes from a few examples provided by a user. The placement of a shape is modeled as an oriented bounding box. Simple geometric relationships between this bounding box and nearby scene polygons define a feature set for the placement. The feature sets of all example placements are then used to learn a probabilistic model over all possible placements and scenes. With this model, we can generate a new set of placements with similar geometric relationships in any given scene. We introduce extensions that enable propagation and generation of shapes in 3D scenes, as well as the application of a learned modeling session to large scenes without additional user interaction. These concepts allow us to generate complex scenes with thousands of objects with relatively little user interaction.

With the emergence of affordable 3D displays, stereoscopy is becoming a commodity. However, often users report discomfort even after brief exposures to stereo content. One of the main reasons is the conflict between vergence and accommodation that is caused by 3D displays. We investigate dynamic adjustment of stereo parameters in a scene using gaze data in order to reduce discomfort. In a user study, we measured stereo fusion times after abrupt manipulation of disparities using gaze data. We found that gaze-controlled manipulation of disparities can lower fusion times for large disparities. In addition we found that gaze-controlled disparity adjustment should be applied in a personalized manner and ideally performed only at the extremities or outside the comfort zone of subjects. These results provide important insight on the problems associated with fast disparity manipulation and are essential for developing appealing gaze-contingent and gaze-controlled applications.

Abstract We present a novel framework for the automatic generation of tourist brochures that include routing instructions and additional information presented in the form of so‐called detail lenses. The first contribution of this paper is the automatic creation of layouts for the brochures. Our approach is based on the minimization of an energy function that combines multiple goals: positioning of the lenses as close as possible to the corresponding region shown in an overview map, keeping the number of lenses low, and an efficient numbering of the lenses. The second contribution is a route‐aware simplification of the graph of streets used for traveling between the points of interest (POIs). This is done by reducing the graph consisting of all shortest paths through the minimization of an energy function. The output is a subset of street segments that enable traveling between all the POIs without considerable detours, while at the same time guaranteeing a clutter‐free visualization.

Stimuli obtained from highly dynamic 3D virtual environments and synchronous eye-tracking data are commonly used by algorithms that strive to correlate gaze to scene objects, a process referred to as gaze-to-object mapping (GTOM) . We propose to address this problem with a probabilistic approach using Bayesian inference. The desired result of the inference is a predicted probability density function (PDF) specifying for each object in the scene a probability to be attended by the user. To evaluate the quality of a predicted attention PDF, we present a methodology to assess the information value (i.e., likelihood) in the predictions of different approaches that can be used to infer object attention. To this end, we propose an experiment based on a visual search task, which allows us to determine the object of attention at a certain point in time under controlled conditions. We perform this experiment with a wide range of static and dynamic visual scenes to obtain a ground-truth evaluation dataset, allowing us to assess GTOM techniques in a set of 30 particularly challenging cases.

We performed a perceptual user study of algorithms that approximate soft shadows in real time. Although a huge body of soft-shadow algorithms have been proposed, to our knowledge this is the first methodical study for comparing different real-time shadow algorithms with respect to their plausibility and visual appearance. We evaluated soft-shadow properties like penumbra overlap with respect to their relevance to shadow perception in a systematic way, and we believe that our results can be useful to guide future shadow approaches in their methods of evaluation. In this study, we also capture the predominant case of an inexperienced user observing shadows without comparing to a reference solution, such as when watching a movie or playing a game. One important result of this experiment is to scientifically verify that real-time soft-shadow algorithms, despite having become physically based and very realistic, can nevertheless be intuitively distinguished from a correct solution by untrained users.

We propose a method for propagating edit operations in 2D vector graphics, based on geometric relationship functions. These functions quantify the geometric relationship of a point to a polygon, such as the distance to the boundary or the direction to the closest corner vertex. The level sets of the relationship functions describe points with the same relationship to a polygon. For a given query point, we first determine a set of relationships to local features, construct all level sets for these relationships, and accumulate them. The maxima of the resulting distribution are points with similar geometric relationships. We show extensions to handle mirror symmetries, and discuss the use of relationship functions as local coordinate systems. Our method can be applied, for example, to interactive floorplan editing, and it is especially useful for large layouts, where individual edits would be cumbersome. We demonstrate populating 2D layouts with tens to hundreds of objects by propagating relatively few edit operations.

With better and faster acquisition devices comes a demand for fast robust reconstruction algorithms, but no L 1 -based technique has been fast enough for online use so far. In this paper, we present a novel continuous formulation of the weighted locally optimal projection (WLOP) operator based on a Gaussian mixture describing the input point density. Our method is up to 7 times faster than an optimized GPU implementation of WLOP, and achieves interactive frame rates for moderately sized point clouds. We give a comprehensive quality analysis showing that our continuous operator achieves a generally higher reconstruction quality than its discrete counterpart. Additionally, we show how to apply our continuous formulation to spherical mixtures of normal directions, to also achieve a fast robust normal reconstruction.

In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets.

We propose a new method for the fast computation of light maps using a many-light global-illumination solution. A complete scene can be light mapped on the order of seconds to minutes, allowing fast and consistent previews for editing or even generation at loading time. In our method, virtual point lights are clustered into a set of virtual polygon lights, which represent a compact description of the illumination in the scene. The actual light-map generation is performed directly on the GPU. Our approach degrades gracefully, avoiding objectionable artifacts even for very short computation times.

We propose a novel way to efficiently calculate soft shadows in real-time applications by overcoming the high computational effort involved with the complex corresponding visibility estimation each frame: We exploit the temporal coherence prevalent in typical scene movement, making the estimation of a new shadow value only necessary whenever regions are newly disoccluded due to camera adjustment, or the shadow situation changes due to object movement. By extending the typical shadow mapping algorithm by an additional light-weight buffer for the tracking of dynamic scene objects, we can robustly and efficiently detect all screen space fragments that need to be updated, including not only the moving objects themselves, but also the soft shadows they cast. By applying this strategy to the popular Percentage Closer Soft Shadow algorithm (PCSS), we double rendering performance in scenes with both static and dynamic objects -- as prevalent in various 3D game levels -- while maintaining the visual quality of the original approach.

Abstract This paper presents a parallel, implementation‐friendly analytic visibility method for triangular meshes. Together with an analytic filter convolution, it allows for a fully analytic solution to anti‐aliased 3D mesh rendering on parallel hardware. Building on recent works in computational geometry, we present a new edge‐triangle intersection algorithm and a novel method to complete the boundaries of all visible triangle regions after a hidden line elimination step. All stages of the method are embarrassingly parallel and easily implementable on parallel hardware. A GPU implementation is discussed and performance characteristics of the method are shown and compared to traditional sampling‐based rendering methods.

Abstract We present an algorithm for artistically modifying physically based shadows. With our tool, an artist can directly edit the shadow boundaries in the scene in an intuitive fashion similar to freeform curve editing. Our algorithm then makes these shadow edits consistent with respect to varying light directions and scene configurations, by creating a shadow mesh from the new silhouettes. The shadow mesh helps a modified shadow volume algorithm cast shadows that conform to the artistic shadow boundary edits, while providing plausible interaction with dynamic environments, including animation of both characters and light sources. Our algorithm provides significantly more fine‐grained local and direct control than previous artistic light editing methods, which makes it simple to adjust the shadows in a scene to reach a particular effect, or to create interesting shadow shapes and shadow animations. All cases are handled with a single intuitive interface, be it soft shadows, or (self‐)shadows on arbitrary receivers.

Abstract This paper provides a comprehensive overview of urban reconstruction. While there exists a considerable body of literature, this topic is still under active research. The work reviewed in this survey stems from the following three research communities: computer graphics, computer vision and photogrammetry and remote sensing. Our goal is to provide a survey that will help researchers to better position their own work in the context of existing solutions, and to help newcomers and practitioners in computer graphics to quickly gain an overview of this vast field. Further, we would like to bring the mentioned research communities to even more interdisciplinary work, since the reconstruction problem itself is by far not solved.

In this article, we introduce a novel reconstruction and modeling pipeline to create polygonal models from unstructured point clouds. We propose an automatic polygonal reconstruction that can then be interactively refined by the user. An initial model is automatically created by extracting a set of RANSAC-based locally fitted planar primitives along with their boundary polygons, and then searching for local adjacency relations among parts of the polygons. The extracted set of adjacency relations is enforced to snap polygon elements together, while simultaneously fitting to the input point cloud and ensuring the planarity of the polygons. This optimization-based snapping algorithm may also be interleaved with user interaction. This allows the user to sketch modifications with coarse and loose 2D strokes, as the exact alignment of the polygons is automatically performed by the snapping. The generated models are coarse, offer simple editing possibilities by design, and are suitable for interactive 3D applications like games, virtual environments, etc. The main innovation in our approach lies in the tight coupling between interactive input and automatic optimization, as well as in an algorithm that robustly discovers the set of adjacency relations.

Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.

In this paper, we present a novel rendering method which integrates reflective or refractive objects into a differential instant radiosity (DIR) framework usable for mixed-reality (MR) applications. This kind of objects are very special from the light interaction point of view, as they reflect and refract incident rays. Therefore they may cause high-frequency lighting effects known as caustics. Using instant-radiosity (IR) methods to approximate these high-frequency lighting effects would require a large amount of virtual point lights (VPLs) and is therefore not desirable due to real-time constraints. Instead, our approach combines differential instant radiosity with three other methods. One method handles more accurate reflections compared to simple cubemaps by using impostors. Another method is able to calculate two refractions in real-time, and the third method uses small quads to create caustic effects. Our proposed method replaces parts in light paths that belong to reflective or refractive objects using these three methods and thus tightly integrates into DIR. In contrast to previous methods which introduce reflective or refractive objects into MR scenarios, our method produces caustics that also emit additional indirect light. The method runs at real-time frame rates, and the results show that reflective and refractive objects with caustics improve the overall impression for MR scenarios.

Abstract We introduce a low‐cost and compact spectral imaging camera design based onunmodifiedconsumer cameras and a custom camera objective. The device can be used in a high‐resolution configuration that measures the spectrum of a column of an imaged scene with up to 0.8 nm spectral resolution, rivalling commercial non‐imaging spectrometers, and a mid‐resolution hyper spectral mode that allows the spectral measurement of a whole image, with up to 5 nm spectral resolution and 120×120 spatial resolution. We develop the necessary calibration methods based on halogen/fluorescent lamps and laser pointers to acquire all necessary information about the optical system. We also derive the mathematical methods to interpret and reconstruct spectra directly from the Bayer array images of a standard RGGB camera. This objective design introduces accurate spectral remote sensing to computational photography, with numerous applications in color theory, colorimetry, vision and rendering, making the acquisition of a spectral image as simple as taking a high‐dynamic‐range image.

Abstract We propose an efficient and light‐weight solution for rendering smooth shadow boundaries that do not reveal the tessellation of the shadow‐casting geometry. Our algorithm reconstructs the smooth contours of the underlying mesh and then extrudes shadow volumes from the smooth silhouettes to render the shadows. For this purpose we propose an improved silhouette reconstruction using the vertex normals of the underlying smooth mesh. Then our method subdivides the silhouette loops until the contours are sufficiently smooth and project to smooth shadow boundaries. This approach decouples the shadow smoothness from the tessellation of the geometry and can be used to maintain equally high shadow quality for multiple LOD levels. It causes only a minimal change to the fill rate, which is the well‐known bottleneck of shadow volumes, and hence has only small overhead.

Abstract We propose a novel interactive framework for modeling building façades from images. Our method is based on the notion of coherence‐based editing which allows exploiting partial symmetries across the façade at any level of detail. The proposed workflow mixes manual interaction with automatic splitting and grouping operations based on unsupervised cluster analysis. In contrast to previous work, our approach leads to detailed 3d geometric models with up to several thousand regions per façade. We compare our modeling scheme to others and evaluate our approach in a user study with an experienced user and several novice users.

Abstract Nowadays, there is a strong trend towards rendering to higher‐resolution displays and at high frame rates. This development aims at delivering more detail and better accuracy, but it also comes at a significant cost. Although graphics cards continue to evolve with an ever‐increasing amount of computational power, the speed gain is easily counteracted by increasingly complex and sophisticated shading computations. For real‐time applications, the direct consequence is that image resolution and temporal resolution are often the first candidates to bow to the performance constraints (e.g. although full HD is possible, PS3 and XBox often render at lower resolutions). In order to achieve high‐quality rendering at a lower cost, one can exploit temporal coherence (TC). The underlying observation is that a higher resolution and frame rate do not necessarily imply a much higher workload, but a larger amount of redundancy and a higher potential for amortizing rendering over several frames. In this survey, we investigate methods that make use of this principle and provide practical and theoretical advice on how to exploit TC for performance optimization. These methods not only allow incorporating more computationally intensive shading effects into many existing applications, but also offer exciting opportunities for extending high‐end graphics applications to lower‐spec consumer‐level hardware. To this end, we first introduce the notion and main concepts of TC, including an overview of historical methods. We then describe a general approach, image‐space reprojection, with several implementation algorithms that facilitate reusing shading information across adjacent frames. We also discuss data‐reuse quality and performance related to reprojection techniques. Finally, in the second half of this survey, we demonstrate various applications that exploit TC in real‐time rendering.

We present a novel adaptive color mapping method for virtual objects in mixed-reality environments. In several mixed-reality applications, added virtual objects should be visually indistinguishable from real objects. Recent mixed-reality methods use global-illumination algorithms to approach this goal. However, simulating the light distribution is not enough for visually plausible images. Since the observing camera has its very own transfer function from real-world radiance values to RGB colors, virtual objects look artificial just because their rendered colors do not match with those of the camera. Our approach combines an on-line camera characterization method with a heuristic to map colors of virtual objects to colors as they would be seen by the observing camera. Previous tone-mapping functions were not designed for use in mixed-reality systems and thus did not take the camera-specific behavior into account. In contrast, our method takes the camera into account and thus can also handle changes of its parameters during runtime. The results show that virtual objects look visually more plausible than by just applying tone-mapping operators.

We propose a novel method for efficient construction of shadow maps by culling shadow casters which do not contribute to visible shadows. The method uses a mask of potential shadow receivers to cull shadow casters using a hierarchical occlusion culling algorithm. We propose several variants of the receiver mask implementations with different culling efficiency and computational costs. For scenes with statically focused shadow maps we designed an efficient strategy to incrementally update the shadow map, which comes close to the rendering performance for unshadowed scenes. We show that our method achieves 3x-10x speedup for rendering large city like scenes and 1.5x-2x speedup for rendering an actual game scene.

Abstract In this paper, we present new solutions for the interactive modeling of city layouts that combine the power of procedural modeling with the flexibility of manual modeling. Procedural modeling enables us to quickly generate large city layouts, while manual modeling allows us to hand‐craft every aspect of a city. We introduce transformation and merging operators for both topology preserving and topology changing transformations based on graph cuts. In combination with a layering system, this allows intuitive manipulation of urban layouts using operations such as drag and drop, translation, rotation etc. In contrast to previous work, these operations always generate valid, i.e., intersection‐free layouts. Furthermore, we introduce anchored assignments to make sure that modifications are persistent even if the whole urban layout is regenerated.

Abstract Because of its versatility, speed and robustness, shadow mapping has always been a popular algorithm for fast hard shadow generation since its introduction in 1978, first for offline film productions and later increasingly so in real‐time graphics. So it is not surprising that recent years have seen an explosion in the number of shadow map related publications. Because of the abundance of articles on the topic, it has become very hard for practitioners and researchers to select a suitable shadow algorithm, and therefore many applications miss out on the latest high‐quality shadow generation approaches. The goal of this survey is to rectify this situation by providing a detailed overview of this field. We show a detailed analysis of shadow mapping errors and derive a comprehensive classification of the existing methods. We discuss the most influential algorithms, consider their benefits and shortcomings and thereby provide the readers with the means to choose the shadow algorithm best suited to their needs.

Audio rendering is generally used to increase the realism of virtual environments (VE). In addition, audio rendering may also improve the performance in specific tasks carried out in interactive applications such as games or simulators. In this article we investigate the effect of the quality of sound rendering on task performance in a task which is inherently vision-dominated. The task is a virtual traffic gap-crossing scenario with two elements: first, to discriminate crossable and uncrossable gaps in oncoming traffic, and second, to find the right timing to start crossing the street without an accident. A study was carried out with 48 participants in an immersive virtual environment setup with a large screen and headphones. Participants were grouped into three different scenarios. In the first one, spatialized audio rendering with head-related transfer function (HRTF) filtering was used. The second group was tested with conventional stereo rendering, and the remaining group ran the experiment in a mute condition. Our results give a clear evidence that spatialized audio improves task performance compared to the unimodal mute condition. Since all task-relevant information was in the participants' field-of-view, we conclude that an enhancement of task performance results from a bimodal advantage due to the integration of visual and auditory spatial cues.

In this paper we present a novel plausible realistic rendering method for mixed reality systems, which is useful for many real life application scenarios, like architecture, product visualization or edutainment. To allow virtual objects to seamlessly blend into the real environment, the real lighting conditions and the mutual illumination effects between real and virtual objects must be considered, while maintaining interactive frame rates (20-30fps). The most important such effects are indirect illumination and shadows cast between real and virtual objects. Our approach combines Instant Radiosity and Differential Rendering. In contrast to some previous solutions, we only need to render the scene once in order to find the mutual effects of virtual and real scenes. The dynamic real illumination is derived from the image stream of a fish-eye lens camera. We describe a new method to assign virtual point lights to multiple primary light sources, which can be real or virtual. We use imperfect shadow maps for calculating illumination from virtual point lights and have significantly improved their accuracy by taking the surface normal of a shadow caster into account. Temporal coherence is exploited to reduce flickering artifacts. Our results show that the presented method highly improves the illusion in mixed reality applications and significantly diminishes the artificial look of virtual objects superimposed onto real scenes.

Irradiance normal mapping is a method to combine two popular techniques, light mapping and normal mapping, and is used in games such as Half-Life 2 or Halo 3. This combination allows using low-resolution light caching on surfaces with only a few coefficients which are evaluated by normal maps to render spatial high-frequency changes in the lighting. Though there are dedicated bases for this purpose such as the Half-Life 2 basis, higher order basis functions such as quadratic Spherical Harmonics are needed for an accurate representation. However, a full spherical basis is not needed since the irradiance is stored on the surface of a scene.

Abstract We present a physically based real‐time water simulation and rendering method that brings volumetric foam to the real‐time domain, significantly increasing the realism of dynamic fluids. We do this by combining a particle‐based fluid model that is capable of accounting for the formation of foam with a layered rendering approach that is able to account for the volumetric properties of water and foam. Foam formation is simulated through Weber number thresholding. For rendering, we approximate the resulting water and foam volumes by storing their respective boundary surfaces in depth maps. This allows us to calculate the attenuation of light rays that pass through these volumes very efficiently. We also introduce an adaptive curvature flow filter that produces consistent fluid surfaces from particles independent of the viewing distance.

Abstract Ambient occlusion is a cheap but effective approximation of global illumination. Recently, screen‐space ambient occlusion (SSAO) methods, which sample the frame buffer as a discretization of the scene geometry, have become very popular for real‐time rendering. We present temporal SSAO (TSSAO), a new algorithm which exploits temporal coherence to produce high‐quality ambient occlusion in real time. Compared to conventional SSAO, our method reduces both noise as well as blurring artefacts due to strong spatial filtering, faithfully representing fine‐grained geometric structures. Our algorithm caches and reuses previously computed SSAO samples, and adaptively applies more samples and spatial filtering only in regions that do not yet have enough information available from previous frames. The method works well for both static and dynamic scenes.

Gaze analysis and prediction in interactive virtual environments, such as games, is a challenging topic since the 3D perspective and variations of the viewpoint as well as the current task introduce many variables that affect the distribution of gaze. In this article, we present a novel pipeline to study eye-tracking data acquired from interactive 3D applications. The result of the pipeline is an importance map which scores the amount of gaze spent on each object. This importance map is then used as a heuristic to predict a user's visual attention according to the object properties present at runtime. The novelty of this approach is that the analysis is performed in object space and the importance map is defined in the feature space of high-level properties. High-level properties are used to encode task relevance and other attributes, such as eccentricity, which may have an impact on gaze behavior. The pipeline has been tested with an exemplary study on a first-person shooter game. In particular, a protocol is presented describing the data acquisition procedure, the learning of different importance maps from the data, and finally an evaluation of the performance of the derived gaze predictors. A metric measuring the degree of correlation between attention predicted by the importance map and the actual gaze yielded clearly positive results. The correlation becomes particularly strong when the player is attentive to an in-game task.

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Abstract This paper presents a new method to animate the interaction of a tree with wind both realistically and in real time. The main idea is to combine statistical observations with physical properties in two major parts of tree animation. First, the interaction of a single branch with the forces applied to it is approximated by a novel efficient two step nonlinear deformation method, allowing arbitrary continuous deformations and circumventing the need to segment a branch to model its deformation behavior. Second, the interaction of wind with the dynamic system representing a tree is statistically modeled. By precomputing the response function of branches to turbulent wind in frequency space, the motion of a branch can be synthesized efficiently by sampling a 2D motion texture. Using a hierarchical form of vertex displacement, both methods can be combined in a single vertex shader, fully leveraging the power of modern GPUs to realistically animate thousands of branches and ten thousands of leaves at practically no cost.

In this paper we propose a global visibility algorithm which computes from-region visibility for all view cells simultaneously in a progressive manner. We cast rays to sample visibility interactions and use the information carried by a ray for all view cells it intersects. The main contribution of the paper is a set of adaptive sampling strategies based on ray mutations that exploit the spatial coherence of visibility. Our method achieves more than an order of magnitude speedup compared to per-view cell sampling. This provides a practical solution to visibility preprocessing and also enables a new type of interactive visibility analysis application, where it is possible to quickly inspect and modify a coarse global visibility solution that is constantly refined.

Abstract We present a method for rendering approximate soft shadows and diffuse indirect illumination in dynamic scenes. The proposed method approximates the original scene geometry with a set of tightly fitting spheres. In previous work, such spheres have been used to dynamically evaluate the visibility function to render soft shadows. In this paper, each sphere also acts as a low‐frequency secondary light source, thereby providing diffuse one‐bounce indirect illumination. The method is completely dynamic and proceeds in two passes: In a first pass, the light intensity distribution on each sphere is updated based on sample points on the corresponding object surface and converted into the spherical harmonics basis. In a second pass, this radiance information and the visibility are accumulated to shade final image pixels. The sphere approximation allows us to compute visibility and diffuse reflections of an object at interactive frame rates of over 20 fps for moderately complex scenes.

Abstract We present a new algorithm for efficient occlusion culling using hardware occlusion queries. The algorithm significantly improves on previous techniques by making better use of temporal and spatial coherence of visibility. This is achieved by using adaptive visibility prediction and query batching. As a result of the new optimizations the number of issued occlusion queries and the number of rendering state changes are significantly reduced. We also propose a simple method for determining tighter bounding volumes for occlusion queries and a method which further reduces the pipeline stalls. The proposed method provides up to an order of magnitude speedup over the previous state of the art. The new technique is simple to implement, does not rely on hardware calibration and integrates well with modern game engines.

Abstract In this paper we present a method for automatic interpolation between adjacent discrete levels of detail to achieve smooth LOD changes in image space. We achieve this by breaking the problem into two passes: We render the two LOD levels individually and combine them in a separate pass afterwards. The interpolation is formulated in a way that only one level has to be updated per frame and the other can be reused from the previous frame, thereby causing roughly the same render cost as with simple non interpolated discrete LOD rendering, only incurring the slight overhead of the final combination pass. Additionally we describe customized interpolation schemes using visibility textures. The method was designed with the ease of integration into existing engines in mind. It requires neither sorting nor blending of objects, nor does it introduce any constrains in the LOD used. The LODs can be coplanar, alpha masked, animated, impostors, and intersecting, while still interpolating smoothly.

We introduce a real-time interactive visual editing paradigm for shape grammars, allowing the creation of rulebases from scratch without text file editing. In previous work, shape-grammar based procedural techniques were successfully applied to the creation of architectural models. However, those methods are text based, and may therefore be difficult to use for artists with little computer science background. Therefore the goal was to enable a visual work-flow combining the power of shape grammars with traditional modeling techniques. We extend previous shape grammar approaches by providing direct and persistent local control over the generated instances, avoiding the combinatorial explosion of grammar rules for modifications that should not affect all instances. The resulting visual editor is flexible: All elements of a complex state-of-the-art grammar can be created and modified visually.

Too little shadow map resolution and resulting undersampling artifacts, perspective and projection aliasing, have long been a fundamental problem of shadowing scenes with shadow mapping.

This paper describes a new tool for preprocessed visibility. It puts together view space and object space partitioning in order to control the render cost and memory cost of the visibility description generated by a visibility solver. The presented method progressively refines view space and object space subdivisions while minimizing the associated render and memory costs. Contrary to previous techniques, both subdivisions are driven by actual visibility information. We show that treating view space and object space together provides a powerful method for controlling the efficiency of the resulting visibility data structures.

Shadowing scenes by shadow mapping has long suffered from the fundamental problem of undersampling artifacts due to too low shadow map resolution, leading to so-called perspective and projection aliasing.

Abstract This paper presents a new, simple and practical algorithm to avoid artifacts when switching between discrete levels of detail (LOD) by smoothly blending LOD representations in image space. We analyse the alternatives of conventional alpha‐blending and so‐called late‐switching (the switching of LODs ‘far enough’ from the eye‐point), widely thought to solve the LOD switching discontinuity problem, and conclude that they either do not work in practice, or defeat the concept of LODs. In contrast we show that our algorithm produces visually pleasing blends for static and animated discrete LODs, for discrete LODs with different types of LOD representations (e.g. billboards and meshes) and even to some extent totally different objects with similar spatial extent, with a very small runtime overhead.

This paper addresses the problem of computing the triangles visible from a region in space. The proposed aggressive visibility solution is based on stochastic ray shooting and can take any triangular model as input. We do not rely on connectivity information, volumetric occluders, or the availability of large occluders, and can therefore process any given input scene. The proposed algorithm is practically memoryless, thereby alleviating the large memory consumption problems prevalent in several previous algorithms. The strategy of our algorithm is to use ray mutations in ray space to cast rays that are likely to sample new triangles. Our algorithm improves the sampling efficiency of previous work by over two orders of magnitude.

Impostors are image-based primitives commonly used to replace complex geometry in order to reduce the rendering time needed for displaying complex scenes. However, a big problem is the huge amount of memory required for impostors. This paper presents an algorithm that automatically places impostors into a scene so that a desired frame rate and image quality is always met, while at the same time not requiring enormous amounts of impostor memory. The low memory requirements are provided by a new placement method and through the simultaneous use of other acceleration techniques like visibility culling and geometric levels of detail.

Abstract We present a simple but powerful algorithm for optimizing the usage of hardware occlusion queries in arbitrary complex scenes. Our method minimizes the number of issued queries and reduces the delays due to the latency of query results. We reuse the results of occlusion queries from the last frame in order to initiate and schedule the queries in the next frame. This is done by processing nodes of a spatial hierarchy in a front‐to‐back order and interleaving occlusion queries with rendering of certain previously visible nodes. The proposed scheduling of the queries makes use of spatial and temporal coherence of visibility. Despite its simplicity, the algorithm achieves good culling efficiency for scenes of various types. The implementation of the algorithm is straightforward and it can be easily integrated in existing real‐time rendering packages based on common hierarchical data structures. Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism

This paper presents a new method for the automatic modeling of architecture. Building designs are derived using split grammars, a new type of parametric set grammar based on the concept of shape. The paper also introduces an attribute matching system and a separate control grammar, which offer the flexibility required to model buildings using a large variety of different styles and design ideas. Through the adaptive nature of the design grammar used, the created building designs can either be generic or adhere closely to a specified goal, depending on the amount of data available.

We present an algorithm for visibility preprocessing of urban environments. The algorithm uses a subdivision of line space to analytically calculate a conservative potentially visible set for a given region in the scene. We present a detailed evaluation of our method, including a comparison to another recently published visibility preprocessing algorithm. To the best of our knowledge, the proposed method is the first algorithm that scales to large scenes and efficiently handles large view cells.

We present an online occlusion culling system which computes visibility in parallel to the rendering pipeline. We show how to use point visibility algorithms to quickly calculate a tight potentially visible set (PVS) which is valid for several frames, by shrinking the occluders used in visibility calculations by an adequate amount. These visibility calculations can be performed on a visibility server, possibly a distinct computer communicating with the display host over a local network. The resulting system essentially combines the advantages of online visibility processing and region-based visibility calculations, allowing asynchronous processing of visibility and display operations. We analyze two different types of hardware-based point visibility algorithms and address the problem of bounded calculation time which is the basis for true real-time behavior. Our results show reliable, sustained 60 Hz performance in a walkthrough with an urban environment of nearly 2 million polygons, and a terrain flyover.