Abstract Real-time holographic communication enables immersive remote interaction by transmitting dynamic three-dimensional representations of users and environments, providing a stronger sense of presence than conventional video conferencing. However, the high data throughput requirements of volumetric streaming introduce challenges related to bandwidth variability and heterogeneous device capabilities. This paper presents an end-to-end system for scalable, real-time holographic telepresence, designed to operate within a fixed volumetric data transmission budget. The proposed approach combines importance-driven and semantic-aware filtering to preserve perceptually and interaction-critical details, while degrading less relevant data. We also leverage gesture recognition to automatically identify and emphasize points of interest, enhancing interactivity and realism. Experimental results demonstrate high visual fidelity and responsive performance with low bandwidth requirements, enabling efficient holographic communication for diverse use cases across different platforms.

Abstract Oriented bounding box (OBB) hierarchies can be used instead of hierarchies based on axis‐aligned bounding boxes (AABB), providing tighter fitting to the underlying geometric structures and resulting in improved interference tests, such as ray‐geometry intersections. In this paper, we present a method for the fast, parallel transformation of an existing bounding volume hierarchy (BVH), based on AABBs, into a hierarchy based on oriented bounding boxes. To this end, we parallelise a high‐quality OBB extraction algorithm from the literature to operate as a standalone OBB estimator and further extend it to efficiently build an OBB hierarchy in a bottom up manner. This agglomerative approach allows for fast parallel execution and the formation of arbitrary, high‐quality OBBs in bounding volume hierarchies. The method is fully implemented on the GPU and extensively evaluated with ray intersections.

Abstract Spatial data structures, such as k-d trees and bounding volume hierarchies, are extensively used in computer graphics for the acceleration of spatial queries in ray tracing, nearest neighbour searches and other tasks. Typically, the splitting strategy employed during the construction of such structures is based on the greedy evaluation of a predefined objective function, resulting in a less than optimal subdivision scheme. In this work, for the first time, we propose the use of unsupervised deep learning to infer the structure of a fixed-depth k-d tree from a constant, subsampled set of the input primitives, based on the recursive evaluation of the cost function at hand. This results in high-quality upper spatial hierarchy, inferred in constant time and without paying the intractable price of a fully recursive tree optimisation. The resulting fixed-depth tree can then be further expanded, in parallel, into either a full k-d tree or transformed into a bounding volume hierarchy, with any known conventional tree builder. The approach is generic enough to accommodate different cost functions, such as the popular surface area and volume heuristics. We experimentally validate that the resulting hierarchies have competitive traversal performance with respect to established tree builders, while maintaining minimal overhead in construction times.

Opening design is a major consideration in architectural buildings during early structural layout specification. Decisions regarding the geometric characteristics of windows, skylights, hatches, etc., greatly impact the overall energy efficiency, airflow and appearance of a building, both internally and externally. In this work, we employ a goal-based, illumination-driven approach to opening design using a Bayesian Optimization approach, based on Gaussian Processes. A method is proposed that allows a designer to easily set lighting intentions along with qualitative and quantitative characteristics of desired openings. All parameters are optimized within a cost minimization framework to calculate geometrically feasible, architecturally admissible and aesthetically pleasing openings of any desired shape, while respecting the designer's lighting constraints.

Abstract In the past few years, advances in graphics hardware have fuelled an explosion of research and development in the field of interactive and real‐time rendering in screen space. Following this trend, a rapidly increasing number of applications rely on multifragment rendering solutions to develop visually convincing graphics applications with dynamic content. The main advantage of these approaches is that they encompass additional rasterised geometry, by retaining more information from the fragment sampling domain, thus augmenting the visibility determination stage. With this survey, we provide an overview of and insight into the extensive, yet active research and respective literature on multifragment rendering. We formally present the multifragment rendering pipeline, clearly identifying the construction strategies, the core image operation categories and their mapping to the respective applications. We describe features and trade‐offs for each class of techniques, pointing out GPU optimisations and limitations and provide practical recommendations for choosing an appropriate method for each application. Finally, we offer fruitful context for discussion by outlining some existing problems and challenges as well as by presenting opportunities for impactful future research directions.

Abstract Lighting plays a very important role in interior design. However, in the specific problem of furniture layout recommendation, illumination has been either neglected or addressed with empirical or very simplified solutions. The effectiveness of a particular layout in its expected task performance can be greatly affected by daylighting and artificial illumination in a non‐trivial manner. In this paper, we introduce a robust method for furniture layout optimization guided by illumination constraints. The method takes into account all dominant light sources, such as sun light, skylighting and fixtures, while also being able to handle movable light emitters. For this task, the method introduces multiple generic illumination constraints and physically‐based light transport estimators, operating alongside typical geometric design guidelines, in a unified manner. We demonstrate how to produce furniture arrangements that comply with important safety, comfort and efficiency illumination criteria, such as glare suppression, under complex light‐environment interactions, which are very hard to handle using empirical or simplified models.

Panoramic, or 360° video streaming and playback are prime components of mixed-reality and panoramic movie-viewing experiences, they offer an immersive viewing experience, and they are becoming increasingly popular, albeit very resource-demanding. Caching of 360° video content at caches close to the user reduces content delivery delay and bandwidth consumption. In 360° video streaming, the recently proposed tiling approach allows the streaming of different parts (tiles) of the 360° content at different resolutions as opposed to monolithic single-stream transmission.

Abstract In this paper we propose an effective technique for the automatic arrangement of spot lights and other luminaires on or near user‐provided arbitrary mounting surfaces in order to highlight the geometric details of complex objects. Since potential applications include the lighting design for exhibitions and similar installations, the method takes into account obstructing geometry and potential occlusion from visitors and other non‐permanent blocking geometry. Our technique generates the most appropriate position and orientation for light sources based on a local contrast maximization near salient geometric features and a clustering mechanism, producing consistent and view‐independent results, with minimal user intervention. We validate our method with realistic test cases including multiple and disjoint exhibits as well as high occlusion scenarios.

We introduce a generic method for interactive ray tracing, able to support complex and dynamic environments, without the need for precomputations or the maintenance of additional spatial data structures. Our method, which relies entirely on the rasterization pipeline, stores fragment information for the entire scene on a multiview and multilayer structure and marches through depth layers to capture both near and distant information for illumination computations. Ray tracing is efficiently achieved by concurrently traversing a novel cube-mapped A-buffer variant in image space that exploits GPU-accelerated double linked lists, decoupled storage, uniform depth subdivision and empty space skipping on a per-fragment basis. We illustrate the effectiveness and quality of our approach on path tracing and ambient occlusion implementations in scenarios, where full scene coverage is of major importance. Finally, we report on the performance and memory usage of our pipeline and compare it against GPGPU ray tracing approaches.

In the last decade, significant research has been conducted for addressing the problem of multi-fragment rendering from different perspectives. While the hardware-accelerated A-buffer is the dominant structure for holding multiple fragments via per-pixel linked lists, several variants have been proposed to alleviate the cost of excessive allocation and random access of video-memory. k-buffer is a widely-accepted A-buffer approximation, able to capture the k-closest to the viewer fragments, due to its reduced memory and computation requirements. To alleviate contention of distant fragments when rendering highly-complex scenes, k+-buffer [Vasilakis and Fudos 2014] concurrently performs culling checks to efficiently discard fragments that are farther from all currently maintained fragments. Unfortunately, the fragment elimination process is performed inside the pixel shader execution, thus not exploiting the performance gain of hardware-accelerated early-Z culling. Furthermore, it depends on the fragment arrival order and requires the insertion of k fragments to start performing any culling tests.

We present a new method for the completion of partial globally-symmetric 3D objects, based on the detection of partial and approximate symmetries in the incomplete input dataset. In our approach, symmetry detection is formulated as a constrained sparsity maximization problem, which is solved efficiently using a robust RANSAC-based optimizer. The detected partial symmetries are then reused iteratively, in order to complete the missing parts of the object. A global error relaxation method minimizes the accumulated alignment errors and a non-rigid registration approach applies local deformations in order to properly handle approximate symmetry. Unlike previous approaches, our method does not rely on the computation of features, it uniformly handles translational, rotational and reflectional symmetries and can provide plausible object completion results, even on challenging cases, where more than half of the target object is missing. We demonstrate our algorithm in the completion of 3D scans with varying levels of partiality and we show the applicability of our approach in the repair and completion of heavily eroded or incomplete cultural heritage objects.

Depth-sorted fragment determination is fundamental for a host of image-based techniques which simulates complex rendering effects. It is also a challenging task in terms of time and space required when rasterizing scenes with high depth complexity. When low graphics memory requirements are of utmost importance, k-buffer can objectively be considered as the most preferred framework which advantageously ensures the correct depth order on a subset of all generated fragments. Although various alternatives have been introduced to partially or completely alleviate the noticeable quality artifacts produced by the initial k-buffer algorithm in the expense of memory increase or performance downgrade, appropriate tools to automatically and dynamically compute the most suitable value of k are still missing. To this end, we introduce k(+)-buffer, a fast framework that accurately simulates the behavior of k-buffer in a single rendering pass. Two memory-bounded data structures: (i) the max-array and (ii) the max-heap are developed on the GPU to concurrently maintain the k-foremost fragments per pixel by exploring pixel synchronization and fragment culling. Memory-friendly strategies are further introduced to dynamically (a) lessen the wasteful memory allocation of individual pixels with low depth complexity frequencies, (b) minimize the allocated size of k-buffer according to different application goals and hardware limitations via a straightforward depth histogram analysis and (c) manage local GPU cache with a fixed-memory depth-sorting mechanism. Finally, an extensive experimental evaluation is provided demonstrating the advantages of our work over all prior k-buffer variants in terms of memory usage, performance cost and image quality.

Screen-space ambient occlusion and obscurance (AO) techniques have become de-facto methods for ambient light attenuation and contact shadows in real-time rendering. Although extensive research has been conducted to improve the quality and performance of AO techniques, view-dependent artifacts remain a major issue. This paper introduces Multi-view Ambient Occlusion, a generic per-fragment view weighting scheme for evaluating screen-space occlusion or obscurance using multiple, arbitrary views, such as the readily available shadow maps. Additionally, it exploits the resulting weights to perform adaptive sampling, based on the importance of each view to reduce the total number of samples, while maintaining the image quality. Multi-view Ambient Occlusion improves and stabilizes the screen-space AO estimation without overestimating the results and can be combined with a variety of existing screen-space AO techniques. We demonstrate the results of our sampling method with both open volume- and solid angle-based AO algorithms.

We present a new fixed-rate texture compression scheme based on the energy compaction properties of the Discrete Wavelet Transform. Targeting existing commodity graphics hardware and APIs, our method is using the DXT compression formats to perform the quantization and storage of the wavelet transform coefficients, ensuring very fast decoding speeds. An optimization framework minimizes the quantization error of the coefficients and improves the overall compression quality. Our method provides a variety of low bitrate encoding modes for the compression of grayscale and color textures. These encoding modes offer either improved quality or reduced storage over the DXT1 format. Furthermore, anisotropic texture filtering is performed efficiently with the help of the native texture hardware. The decoding speed and the simplicity of the implementation make our approach well suited for use in games and other interactive applications.

Abstract In this paper we introduce a new fixed‐rate texture compression scheme based on the energy compaction properties of a modified Haar transform. The coefficients of this transform are quantized and stored using standard block compression methods, such as DXTC and BC7, ensuring simple implementation and very fast decoding speeds. Furthermore, coefficients with the highest contribution to the final image are quantized with higher accuracy, improving the overall compression quality. The proposed modifications to the standard Haar transform, along with a number of additional optimizations, improve the coefficient quantization and reduce the compression error. The resulting method offers more flexibility than the currently available texture compression formats, providing a variety of additional low bitrate encoding modes for the compression of grayscale and color textures.

The quality of the available hardware texture filtering, even on state of the art graphics hardware, suffers from several aliasing artifacts, in both spatial and temporal domain. Those artifacts are mostly evident in extreme conditions, such as grazing viewing angles, highly warped texture coordinates, or extreme perspective and become especially annoying when animation is involved.

Real-time rendering can benefit from global illumination methods to make the 3D environments look more convincing and lifelike. On the other hand, the conventional global illumination algorithms for the estimation of the diffuse surface interreflection make heavy usage of intra- and interobject visibility calculations, so they are time-consuming, and using them in real-time graphics applications can be prohibitive for complex scenes. Modern illumination approximations, such as ambient occlusion variants, use precalculated or frame-dependent data to reduce the problem to a local shading one. This paper presents a fast real-time method for visibility sampling using volumetric data in order to produce accurate inter- and intraobject ambient occlusion. The proposed volume sampling technique disassociates surface representation data from the visibility calculations, and therefore, makes the method suitable for both primitive-order or screen-order rendering, such as deferred rendering. The sampling mechanism can be used in any application that performs visibility queries or ray marching.

In this tutorial we will present the infrastructure required, both software and hardware, to create the Virtual Reality (VR) illusion. The history and the application areas of VR will be presented. From the software required to the image generator to the different display systems -- both head based and projection based -- all components of a VR system as well as practical deployment issues will be investigated. The stereo depth principle will be explained along with the different stereo methodologies available today. Aspects of a VR experience like immersion and collaboration will be explored. Other topics include the physical interface and interaction devices and the methods of manipulating a Virtual Environment by tracking users and devices.An attempt will be made to differentiate VR from pre-rendered Computer Graphics by presenting the issues concerning Real Time graphics. Finally possible future developments in the areas of Virtual Reality technology and Virtual Environments will be presented.

As the interest of the public for new forms of media grows, museums and theme parks select real time Virtual Reality productions as their presentation medium. Based on three-dimensional graphics, interaction, sound, music and intense story telling they mesmerize their audiences. The Foundation of the Hellenic World (FHW) having opened so far to the public three different Virtual Reality theaters, is in the process of building a new Dome-shaped Virtual Reality theatre with a capacity of 130 people. This fully interactive theatre will present new experiences in immersion to the visitors. In this paper we present the challenges encountered in developing productions for such a large spherical display system as well as building the underlying real-time display and support systems.

The problem of re-assembling an object from its parts or fragments has never been addressed with a unified computational approach, which depends on the pure geometric form of the parts and not on application-specific features. We propose a method for the automatic reconstruction of a model based on the geometry of its parts, which may be computer-generated models or range-scanned models. The matching process can benefit from any other external constraint imposed by the specific application.

Polygonal models are the most common representation of structured 3D data in computer graphics, pattern recognition and machine vision. The method presented here automatically identifies and labels all compact surface regions of a polygonal mesh, visible or not, and extracts valuable invariant features regarding their geometric attributes. A method that is independent of the mesh topology is also presented for the surface bumpiness estimation and the identification of coarse surface regions.