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An Attempt to Segment Foreground in Dynamic Scenes

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Advances in Visual Computing (ISVC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6938))

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Abstract

In general, human behavior analysis relies on a sequence of human segments, e.g. gait recognition aims to address human identification based on people’s manners of walking, and thus relies on the segmented silhouettes. Background subtraction is the most widely used approach to segment foreground, while dynamic scenes make it difficult to work. In this paper, we propose to combine Mean-Shift-based tracking with adaptive scale and Graph-cuts-based segmentation with label propagation. The average precision on a number of sequences is 0.82, and the average recall is 0.72. Besides, our method only requires weak user interaction and is computationally efficient. We compare our method with its variant without label propagation, as well as GrabCut. For the tracking module only, we compare Mean Shift with several state-of-the-art methods (i.e. OnlineBoost, SemiBoost, MILTrack, FragTrack).

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Authors and Affiliations

  1. Key Lab of Intelligent Information Processing of CAS, Institute of Computing Technology, Chinese Academy of Sciences (CAS), Beijing, China

    Xiang Xiang

Authors
  1. Xiang Xiang
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Editor information

Editors and Affiliations

  1. University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, 89512, Reno, NV, USA

    Darko Koracin

  5. Department of Computer Science and Engineering, University of South Carolina, 29208, Columbia, SC, USA

    Song Wang

  6. HRL Laboratories, 3011 Malibu Canyon Road, 90265-4797, Malibu, CA, USA

    Kim Kyungnam

  7. Purdue University, 47907-2021, West Lafayette, IN, USA

    Bedrich Benes

  8. Sandia National Laboratory, 87185, Albuquerque, NM, USA

    Kenneth Moreland

  9. University of Louisiana, 70504, Lafayette, LA, USA

    Christoph Borst

  10. Adobe Systems Incorporated, San Francisco, CA, USA

    Stephen DiVerdi

  11. Polytechnic Institute of NYU, 11201, Brooklyn, NY, USA

    Chiang Yi-Jen

  12. Lawrence Livermore National Laboratory, 94551-0808, Livermore, CA, USA

    Jiang Ming

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© 2011 Springer-Verlag Berlin Heidelberg

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Xiang, X. (2011). An Attempt to Segment Foreground in Dynamic Scenes. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24028-7_12

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  • DOI: https://doi.org/10.1007/978-3-642-24028-7_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24027-0

  • Online ISBN: 978-3-642-24028-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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