Skip to main content

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

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5359))

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.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. SourceForge.net: Open Computer Vision Library, http://sourceforge.net/projects/opencvlibrary

  2. Fernando, R., Kilgard, M.: The Definitive Guide to Programmable Real-Time Graphics. Addison-Wesley Longman Publishing Co., Inc., Boston (2003)

    Google Scholar 

  3. Rost, R.: OpenGL Shading Language. Addison-Wesley professional, Reading (2004)

    Google Scholar 

  4. 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)

    Google Scholar 

  5. Mac Cool, M., Du Toit, S.: Metaprogramming GPUs with Sh. AK Peters, Inc. (2004)

    Google Scholar 

  6. Buck, I., et al.: BrookGPU (2003), http://graphics.stanford.edu/projects/brookgpu/

  7. NVIDIA: CUDA (Compute Unified Device Architecture) (2006), http://www.nvidia.com/object/cuda_home.html

  8. AMD/ATI: CTM (Close To Metal) (2007), http://ati.amd.com/companyinfo/researcher/documents/ATI_CTM_Guide.pdf

  9. Hopf, M., Ertl, T.: Hardware-Based Wavelet Transformations. In: Workshop of Vision, Modelling, and Visualization (VMV 1999), pp. 317–328 (1999)

    Google Scholar 

  10. Yaromenok, A.: DIPlib - Digital Image Processing Library (2003), http://sourceforge.net/projects/diplib

  11. 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)

    Google Scholar 

  12. Jargstorff, F.: A framework for image processing. In: GPU Gems, vol. 1, pp. 445–467. Addison Wesley professional, Reading (2004)

    Google Scholar 

  13. Nocent, O.: Image processing with OpenGL (2004), http://leri.univ-reims.fr/nocent/gpu.html

  14. Fung, J., et al.: OpenVIDIA: Parallel GPU Computer Vision (2004 and later on), http://openvidia.sourceforge.net

  15. Moreland, K., Angel, E.: The FFT on a GPU. In: SIGGRAPH/Eurographics Workshop on Graphics Hardware, pp. 112–119 (2003)

    Google Scholar 

  16. 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)

    Google Scholar 

  17. Strzodka, R., Garbe, C.: Real-time motion estimation and visualization on graphics cards. In: Proc. IEEE Visualization, pp. 545–552 (2004)

    Google Scholar 

  18. Fernando, R.: GPU Gems: Programming techniques, Tips and Tricks for Real-Time Graphics. Addison Wesley professional, Reading (2004)

    Google Scholar 

  19. Hubert Nguyen, N.C. (ed.): Programming Techniques for High-Performance Graphics and General-Purpose. Addison Wesley professional, Reading (2007)

    Google Scholar 

  20. GPU4Vision (2008), http://www.gpu4vision.org

  21. Harris, M.: SC07 - High Performance Computing with CUDA - Optimizing CUDA (2007), http://www.gpgpu.org/sc2007/SC07_CUDA_5_Optimization_Harris.pdf

  22. Allusse, Y.: SugoiTracer library: tools for embedded application benchmarking (2006), http://sourceforge.net/projects/sugoitools/

  23. 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)

    Google Scholar 

  24. 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)

    Google Scholar 

  25. NVIDIA: CUDPP(CUDA Data Parallel Primitives Library) (2006), http://www.gpgpu.org/developer/cudpp/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

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

Download citation

  • 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

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics