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A GPU-Based Statistical Framework for Moving Object Segmentation: Implementation, Analysis and Applications

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Internet and Distributed Computing Systems (IDCS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9258))

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Abstract

This paper describes a real-time implementation of a recently proposed background maintenance algorithm and reports the relative performances. Experimental results on dynamic scenes taken from a fixed camera show that the proposed parallel algorithm produces background images with an improved quality with respect to classical pixel-wise algorithms, obtaining a speedup of more than 35 times compared to CPU implementation. It is worth noting that we used both the GeForce 9 series (actually a 9800 GPU) available from the year 2008 and the GeForce 200 series (actually a 295 GPU) available from the year 2009. Finally, we show that this parallel implementation allows us to use it in real-time moving object detection application.

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Author information

Authors and Affiliations

  1. DIA Department, University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea & Enzo Mumolo

  2. ICAR-CNR, Rende, Italy

    Alfredo Cuzzocrea

  3. Chuo University, Tokyo, Japan

    Alessandro Moro & Kazunori Umeda

Authors
  1. Alfredo Cuzzocrea
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  2. Enzo Mumolo
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  3. Alessandro Moro
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  4. Kazunori Umeda
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Corresponding author

Correspondence to Alfredo Cuzzocrea .

Editor information

Editors and Affiliations

  1. School of Systems Engineering, University of Reading, Reading, Berkshire, United Kingdom

    Giuseppe Di Fatta

  2. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, University of Calabria Dipartimento di Ingegneria Informat, Rende, Italy

    Giancarlo Fortino

  3. School of Logistics and Engineer, University of Technology Wuhan, Wuhan, China

    Wenfeng Li

  4. CSIRO ICT, Acton, Australia

    Mukaddim Pathan

  5. School of Systems Engineering, University of Reading, Whiteknights, Reading, United Kingdom

    Frederic Stahl

  6. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, University of Calabria, Rende, Italy

    Antonio Guerrieri

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© 2015 Springer International Publishing Switzerland

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Cuzzocrea, A., Mumolo, E., Moro, A., Umeda, K. (2015). A GPU-Based Statistical Framework for Moving Object Segmentation: Implementation, Analysis and Applications. In: Di Fatta, G., Fortino, G., Li, W., Pathan, M., Stahl, F., Guerrieri, A. (eds) Internet and Distributed Computing Systems. IDCS 2015. Lecture Notes in Computer Science(), vol 9258. Springer, Cham. https://doi.org/10.1007/978-3-319-23237-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-23237-9_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23236-2

  • Online ISBN: 978-3-319-23237-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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