GpuCV: A GPU-accelerated framework for Image Processing and Computer Vision

Yannick Allusse, Patrick Horain, Ankit Agarwal, and Cindula Saipriyadarshan


Publication reference:

Y. Allusse, P. Horain, A. Agarwal, C. Saipriyadarshan, "GpuCV: A GPU-accelerated framework for Image Processing and Computer Vision", Advances in Visual Computing, Proceedings of the 4th International Symposium on Visual Computing (ISVC08), December 1-3, 2008, Las Vegas, Nevada, USA LNCS Volume 5359/2008, Springer-Verlag, p. 430-439 [doi:10.1007/978-3-540-89646-3_42].

Abstract:

This paper presents briefly describes 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.

Full text:

Copyright 2008 Springer-Verlag. The copyright to this Contribution is transferred to Springer-Verlag GmbH Berlin Heidelberg. This article has been published on Springer’s website.
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