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GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision

Yannick Allusse, Patrick Horain, Ankit Agarwal, Cindula Saipriyadarshan
Institut TELECOM; TELECOM & Management SudParis 9, rue Charles Fourier, 91011 Evry Cedex, France
In Advances in Visual Computing, Vol. 5359 (2008), pp. 430-439-439.

@article{allusse2008gpucv,

   title={GpuCV: A GPU-accelerated framework for image processing and computer vision},

   author={Allusse, Y. and Horain, P. and Agarwal, A. and Saipriyadarshan, C.},

   journal={Advances in Visual Computing},

   pages={430–439},

   year={2008},

   publisher={Springer}

}

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.
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