Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
The Cg Tutorial: The Definitive Guide to Programmable Real-Time Graphics
The Cg Tutorial: The Definitive Guide to Programmable Real-Time Graphics
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics
OpenGL(R) Shading Language
Metaprogramming GPUs with Sh
Real-Time Motion Estimation and Visualization on Graphics Cards
VIS '04 Proceedings of the conference on Visualization '04
Generalized distance transforms and skeletons in graphics hardware
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Proceedings of the Conference on Design, Automation and Test in Europe
Easy, fast, and energy-efficient object detection on heterogeneous on-chip architectures
ACM Transactions on Architecture and Code Optimization (TACO)
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This paper presents briefly the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multi-platform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU technologies. GpuCV is designed to be compatible with the popular OpenCV library by offering GPU-accelerated operators that can be integrated into native OpenCV applications. The GpuCV framework transparently manages hardware capabilities, data synchronization, activation of low level GLSL and CUDA programs, on-the-fly benchmarking and switching to the most efficient implementation and finally offers a set of image processing operators with GPU acceleration available.