1,721,006 research outputs found
A High-level Kernel Transformation Rule Set for Efficient Caching on Graphics Hardware - Increasing Streaming Execution Performance with Minimal Design Effort
No full textThis paper proposes a high-level rule set that allows algorithmic designers to optimize their implementation on graphics hardware, with minimal design effort. The rules suggest possible kernel splits and merges to transform the kernels of the original design, resulting in an inter-kernel rather then low-level intra-kernel optimization. The rules consider both traditional texture caches and next-gen shared memory – which are used in the abstract stream-centric paradigms such as CUDA and Brook+ – and can therefore be implicitly applied in most generic streaming applications on graphics hardware
A Scalable End-to-End Optimized Real-Time Image-Based Rendering Framework on Graphics Hardware
No full textThis paper presents the system-level overview of a real-time image-based rendering framework performing multiple intermediate view synthesis, completely on the Graphics Processing Unit (GPU). The software design achieves high-performance, yet maintains flexibility and ease of development through a hierarchical layered architecture. The framework implements the intermediate view synthesis by a chain of consecutive processing modules, as an extension to the Middlebury open software structure, allowing it to benchmark quality and execution time of individual modules for end-to-end system performance optimization. The modules can be flexibly coordinated, enabling scalability to run the multiple view synthesis in real-time on both powerful and weak GPUs
A Scalable End-to-End Optimized Real-Time Image-Based Rendering Framework on Graphics Hardware
No full textThis paper presents the system-level overview of a real-time image-based rendering framework performing multiple intermediate view synthesis, completely on the Graphics Processing Unit (GPU). The software design achieves high-performance, yet maintains flexibility and ease of development through a hierarchical layered architecture. The framework implements the intermediate view synthesis by a chain of consecutive processing modules, as an extension to the Middlebury open software structure, allowing it to benchmark quality and execution time of individual modules for end-to-end system performance optimization. The modules can be flexibly coordinated, enabling scalability to run the multiple view synthesis in real-time on both powerful and weak GPUs
A High-level Kernel Transformation Rule Set for Efficient Caching on Graphics Hardware - Increasing Streaming Execution Performance with Minimal Design Effort
No full textThis paper proposes a high-level rule set that allows algorithmic designers to optimize their implementation on graphics hardware, with minimal design effort. The rules suggest possible kernel splits and merges to transform the kernels of the original design, resulting in an inter-kernel rather then low-level intra-kernel optimization. The rules consider both traditional texture caches and next-gen shared memory – which are used in the abstract stream-centric paradigms such as CUDA and Brook+ – and can therefore be implicitly applied in most generic streaming applications on graphics hardware
Stream-Centric Stereo Matching and View Synthesis: A High-Speed Approach on GPUs
No full textIn this paper, we propose a real-time image-based rendering (IBR) system. It is specifically designed for photorealistic view synthesis at high-speed on the graphics processing unit (GPU). We steer the proposed IBR system design with two high-level ideas. First, for cost-effective IBR, as long as the synthesized views look visually plausible, the estimated disparity and occlusion need not be correct. Hence, we jointly optimize stereo matching and view synthesis for a favorable end-to-end performance. Second, for great real-time acceleration on GPUs, all functional modules need be shaped at an early design stage, fitting the massively parallel streaming architecture of GPUs. Based on these two guidelines, we first propose a stream-centric local stereo matching algorithm. The key idea is to construct a versatile set of variable support patterns in a highly efficient manner, and then an optimal local support pattern is selected to approximate varying image structures adaptively. Next, a low-complexity adaptive view synthesis technique is proposed. It efficiently tackles visual artifacts in synthesized images, using a novel photometric outlier detection and handling scheme. We evaluated both the disparity estimation accuracy and novel view synthesis quality of the proposed approach, based on the benchmark Middlebury stereo datasets. The experiments show that our local stereo method produces consistently reliable disparity estimates for both homogeneous regions and depth discontinuities, outperforming several previous GPU-based local methods. More importantly, visually plausible intermediate views are generated by our IBR approach at high-speed on the GPU. With stereo matching and view synthesis completely running on an NVIDIA GeForce 8800 GT graphics card, the proposed IBR system reaches about 100 f/s for 450x375 stereo images with 60 disparity levels
Free Viewpoint Video for Soccer using Histogram-Based Validity Maps in Plane Sweeping
No full textIn this paper, we present a method to accomplish free viewpoint video for soccer scenes. This will allow the rendering of a virtual camera, such as a virtual rail camera, or a camera moving around a frozen scene. We use 7 static cameras in a wide baseline setup (10 meters apart from each other). After debayering and segmentation, a crude depth map is created using a plane sweep approach. Next, this depth map is filtered and used in a second, depth-selective plane sweep by creating validity maps per depth. The complete method employs NVIDIA CUDA and traditional GPU shaders, resulting in a fast and scalable solution. The results, using real images, show the effective removal of artifacts, yielding high quality images for a virtual camera
Free Viewpoint Video for Soccer using Histogram-Based Validity Maps in Plane Sweeping
No full textIn this paper, we present a method to accomplish free viewpoint video for soccer scenes. This will allow the rendering of a virtual camera, such as a virtual rail camera, or a camera moving around a frozen scene. We use 7 static cameras in a wide baseline setup (10 meters apart from each other). After debayering and segmentation, a crude depth map is created using a plane sweep approach. Next, this depth map is filtered and used in a second, depth-selective plane sweep by creating validity maps per depth. The complete method employs NVIDIA CUDA and traditional GPU shaders, resulting in a fast and scalable solution. The results, using real images, show the effective removal of artifacts, yielding high quality images for a virtual camera
Immersive GPU-driven biological adaptive stereoscopic rendering
No full textIn this paper, we want to sensitize 3D content developers
and researchers of broadening their scope of parameters
they take into account for generating 3D content. State-of-theart perceptual research has already shown that monocular visual cues highly contribute to the very fundamentals of 3D perception, and binocular ones are merely linked to them in order to create a rich depth experience. In this context, we present an overview
of the research concerning our teleconferencing system that is able to recreate biological stereoscopic input, without loosing consistency in all related monocular cues such as accommodation, occlusion, size (gradient), motion parallax, texture gradient and linear perspective. The system adapts in real-time by doing both GPU-driven analysis and rendering, based on the physical parameters of the system user
Immersive GPU-driven biological adaptive stereoscopic rendering
No full textIn this paper, we want to sensitize 3D content developers
and researchers of broadening their scope of parameters
they take into account for generating 3D content. State-of-theart perceptual research has already shown that monocular visual cues highly contribute to the very fundamentals of 3D perception, and binocular ones are merely linked to them in order to create a rich depth experience. In this context, we present an overview
of the research concerning our teleconferencing system that is able to recreate biological stereoscopic input, without loosing consistency in all related monocular cues such as accommodation, occlusion, size (gradient), motion parallax, texture gradient and linear perspective. The system adapts in real-time by doing both GPU-driven analysis and rendering, based on the physical parameters of the system user
MIGRATING REAL-TIME DEPTH IMAGE-BASED RENDERING FROM TRADITIONAL TO NEXT-GEN GPGPU
No full textThis paper focuses on the current revolution in using the GPU for general-purpose computations (GPGPU), and how to maximally exploit its powerful resources. Recently, the advent of next-generation GPGPU replaced the traditional way of exploiting the graphics hardware. We have migrated real-time depth image-based rendering - for use in contemporary 3DTV technology - and noticed however that using both GPGPU paradigms leads to a higher performance than non-hybrid implementations. Using this paper, we want to sensitize other researchers to reconsider before migrating their implementation completely, and use our practical migration rules to achieve maximum performance with minimal effort.This work is supported by the IWT within the Hasselt University under grant number SB071150
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