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IFIP International Conference on Computer Science and its Applications

CIIA 2015: Computer Science and Its Applications pp 54–65Cite as

Multi-CPU/Multi-GPU Based Framework for Multimedia Processing

  • Conference paper

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 456)

Abstract

Image and video processing algorithms present a necessary tool for various domains related to computer vision such as medical applications, pattern recognition and real time video processing methods. The performance of these algorithms have been severely hampered by their high intensive computation since the new video standards, especially those in high definitions require more resources and memory to achieve their computations. In this paper, we propose a new framework for multimedia (single image, multiple images, multiple videos, video in real time) processing that exploits the full computing power of heterogeneous machines. This framework enables to select firstly the computing units (CPU or/and GPU) for processing, and secondly the methods to be applied depending on the type of media to process and the algorithm complexity. The framework exploits efficient scheduling strategies, and allows to reduce significantly data transfer times thanks to an efficient management of GPU memories and to the overlapping of data copies by kernels executions. Otherwise, the framework includes several GPU-based image and video primitive functions, such as silhouette extraction, corners detection, contours extraction, sparse and dense optical flow estimation. These primitives are exploited in different applications such as vertebra segmentation in X-ray and MR images, videos indexation, event detection and localization in multi-user scenarios. Experimental results have been obtained by applying the framework on different computer vision methods showing a global speedup ranging from 5 to 100, by comparison with sequential CPU implementations.

Keywords

  • GPU
  • Heterogeneous architectures
  • Image and video processing
  • Medical imaging
  • Motion tracking

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Computer science department, University of Mons, 20, Place du Parc. Mons, Mons, Belgium

    Sidi Ahmed Mahmoudi & Pierre Manneback

Authors
  1. Sidi Ahmed Mahmoudi
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  2. Pierre Manneback
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Corresponding author

Correspondence to Sidi Ahmed Mahmoudi .

Editor information

Editors and Affiliations

  1. Tahar Moulay University, Saida, Algeria

    Abdelmalek Amine

  2. LIAS/ISAE-ENSMA, Chasseneuil, France

    Ladjel Bellatreche

  3. Sidi Bel Abbès University, Sidi Bel Abbès, Algeria

    Zakaria Elberrichi

  4. University of Vienna, Vienna, Austria

    Erich J. Neuhold

  5. Poznan University of Technology Inst. Computing Science, Poznan, Poland

    Robert Wrembel

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© 2015 IFIP International Federation for Information Processing

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Mahmoudi, S.A., Manneback, P. (2015). Multi-CPU/Multi-GPU Based Framework for Multimedia Processing. In: Amine, A., Bellatreche, L., Elberrichi, Z., Neuhold, E., Wrembel, R. (eds) Computer Science and Its Applications. CIIA 2015. IFIP Advances in Information and Communication Technology, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-19578-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-19578-0_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19577-3

  • Online ISBN: 978-3-319-19578-0

  • eBook Packages: Computer ScienceComputer Science (R0)