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 We present a machine learning approach for efficiently computing order independent transparency (OIT) by deploying a light weight neural network implemented fully on shaders. Our method is fast, requires a small constant amount of memory (depends only on the screen resolution and not on the number of triangles or transparent layers), is more accurate as compared to previous approximate methods, works for every scene without setup and is portable to all platforms running even with commodity GPUs. Our method requires a rendering pass to extract all features that are subsequently used to predict the overall OIT pixel colour with a pre‐trained neural network. We provide a comparative experimental evaluation and shader source code of all methods for reproduction of the experiments.

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.

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.

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.

k-buffer facilitates novel approaches to multi-fragment rendering and visualization for developing interactive applications on the GPU. Various alternatives have been proposed to alleviate its memory hazards and to avoid completely or partially the necessity of geometry pre-sorting. However, that came with the burden of excessive memory allocation and depth precision artifacts. We introduce k+-buffer, a fast and accurate framework that simulates the k-buffer behavior by exploiting fragment culling and pixel synchronization. Two GPU-accelerated data structures have been developed: (i) the max-array and (ii) the max-heap. These memory-bounded data structures accurately maintain the k-foremost fragments per pixel in a single geometry pass. The choice of the data structure depends on the size k (application-dependent). Without any software-redesign, the proposed scheme can be adapted to perform as a Z-buffer or an A-buffer capturing a single or all generated fragments, respectively. A memory-friendly strategy is also proposed, extending the proposed pipeline to dynamically lessen the potential wasteful memory allocation. Finally, an extensive experimental evaluation is provided demonstrating the advantages of k+-buffer over all prior k-buffer variants in terms of memory usage, performance cost and image quality.

Abstract We present a complete approach to efficiently deriving a varying level‐of‐detail segmentation of arbitrary animated objects. An over‐segmentation is built by combining sets of initial segments computed for each input pose, followed by a fast progressive simplification which aims at preserving rigid segments. The final segmentation result can be efficiently adjusted for cases where pose editing is performed or new poses are added at arbitrary positions in the mesh animation sequence. A smooth view of pose‐to‐pose segmentation transitions is offered by merging the partitioning of the current pose with that of the next pose. A perceptually friendly visualization scheme is also introduced for propagating segment colors between consecutive poses. We report on the efficiency and quality of our framework as compared to previous methods under a variety of skeletal and highly deformable mesh animations.

Many applications require operations on multiple fragments that result from ray casting at the same pixel location. To this end, several approaches have been introduced that process for each pixel one or more fragments per rendering pass, so as to produce a multifragment effect. However, multifragment rasterization is susceptible to flickering artifacts when two or more visible fragments of the scene have identical depth values. This phenomenon is called coplanarity or Z-fighting and incurs various unpleasant and unintuitive results when rendering complex multilayer scenes. In this work, we develop depth-fighting aware algorithms for reducing, eliminating and/or detecting related flaws in scenes suffering from duplicate geometry. We adapt previously presented single and multipass rendering methods, providing alternatives for both commodity and modern graphics hardware. We report on the efficiency and robustness of all these alternatives and provide comprehensive comparison results. Finally, visual results are offered illustrating the effectiveness of our variants for a number of applications where depth accuracy and order are of critical importance.

Abstract In this paper, we present a skeletal rigid skinning approach. First, we describe a skeleton extraction technique that produces refined skeletons appropriate for animation from decomposed character models. Then, to avoid the artifacts generated in previous skinning approaches and the associated high training costs, we develop an efficient and robust rigid skinning technique that applies blending patches around joints. To achieve real time animation, we have adapted all steps of our rigid skinning algorithm so that they are performed efficiently on the GPU. Finally, we present an evaluation of our methods against four criteria: efficiency, quality, scope, and robustness. Copyright © 2010 John Wiley & Sons, Ltd.