Abstract
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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SourceForge.net: Open Computer Vision Library, http://sourceforge.net/projects/opencvlibrary
Fernando, R., Kilgard, M.: The Definitive Guide to Programmable Real-Time Graphics. Addison-Wesley Longman Publishing Co., Inc., Boston (2003)
Rost, R.: OpenGL Shading Language. Addison-Wesley professional, Reading (2004)
Peeper, C., Mitchell, J.: Introduction to the DirectX 9 High Level Shading Language. In: ShaderX2 - Introduction and Tutorials with DirectX 9, Wolfgang F. Engel,Wordware Publishing, Inc. (2003)
Mac Cool, M., Du Toit, S.: Metaprogramming GPUs with Sh. AK Peters, Inc. (2004)
Buck, I., et al.: BrookGPU (2003), http://graphics.stanford.edu/projects/brookgpu/
NVIDIA: CUDA (Compute Unified Device Architecture) (2006), http://www.nvidia.com/object/cuda_home.html
AMD/ATI: CTM (Close To Metal) (2007), http://ati.amd.com/companyinfo/researcher/documents/ATI_CTM_Guide.pdf
Hopf, M., Ertl, T.: Hardware-Based Wavelet Transformations. In: Workshop of Vision, Modelling, and Visualization (VMV 1999), pp. 317–328 (1999)
Yaromenok, A.: DIPlib - Digital Image Processing Library (2003), http://sourceforge.net/projects/diplib
Colantoni, P., Boukala, N., Da Rugna, J.: Fast and accurate color image processing using 3d graphics cards. In: 8th International FallWorkshop: Vision Modeling and Visualization, Munich, Germany (2003)
Jargstorff, F.: A framework for image processing. In: GPU Gems, vol. 1, pp. 445–467. Addison Wesley professional, Reading (2004)
Nocent, O.: Image processing with OpenGL (2004), http://leri.univ-reims.fr/nocent/gpu.html
Fung, J., et al.: OpenVIDIA: Parallel GPU Computer Vision (2004 and later on), http://openvidia.sourceforge.net
Moreland, K., Angel, E.: The FFT on a GPU. In: SIGGRAPH/Eurographics Workshop on Graphics Hardware, pp. 112–119 (2003)
Strzodka, R., Telea, A.: Generalized Distance Transforms and skeletons in graphics hardware. In: Proceedings of EG/IEEE TCVG Symposium on Visualization (VisSym 2004), pp. 221–230 (2004)
Strzodka, R., Garbe, C.: Real-time motion estimation and visualization on graphics cards. In: Proc. IEEE Visualization, pp. 545–552 (2004)
Fernando, R.: GPU Gems: Programming techniques, Tips and Tricks for Real-Time Graphics. Addison Wesley professional, Reading (2004)
Hubert Nguyen, N.C. (ed.): Programming Techniques for High-Performance Graphics and General-Purpose. Addison Wesley professional, Reading (2007)
GPU4Vision (2008), http://www.gpu4vision.org
Harris, M.: SC07 - High Performance Computing with CUDA - Optimizing CUDA (2007), http://www.gpgpu.org/sc2007/SC07_CUDA_5_Optimization_Harris.pdf
Allusse, Y.: SugoiTracer library: tools for embedded application benchmarking (2006), http://sourceforge.net/projects/sugoitools/
Deriche, R.: Fast algorithms for low-level vision. In: 9th International Conference on Pattern Recognition, 2007. NSS 2007, vol. 4, pp. 434–438. IEEE, Rome (1988)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR 2001, vol. 1, pp. 511–518 (2001)
NVIDIA: CUDPP(CUDA Data Parallel Primitives Library) (2006), http://www.gpgpu.org/developer/cudpp/
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© 2008 Springer-Verlag Berlin Heidelberg
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Allusse, Y., Horain, P., Agarwal, A., Saipriyadarshan, C. (2008). GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_42
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DOI: https://doi.org/10.1007/978-3-540-89646-3_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
Online ISBN: 978-3-540-89646-3
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