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UMD_VDT, an Integration of Detection and Tracking Methods for Multiple Human Tracking

  • Conference paper
Multimodal Technologies for Perception of Humans (RT 2007, CLEAR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4625))

Abstract

We integrate human detection and regional affine invariant feature tracking into a robust human tracking system. First, foreground blobs are detected using background subtraction. The background model is built with a local predictive model to cope with large illumination changes. Detected foreground blobs are then used by a box tracker to establish stable tracks of moving objects. Human detection hypotheses are detected using a combination of both shape and region information through a hierarchical part-template matching method. Human detection results are then used to refine tracks for moving people. Track refinement, extension and merging are carried out with a robust tracker that is based on regional affine invariant features. We show experimental results for the separate components as well as the entire system.

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Authors and Affiliations

  1. UMIACS, University of Maryland, College Park, MD 20740, USA

    Son Tran, Zhe Lin, David Harwood & Larry Davis

Authors
  1. Son Tran
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  2. Zhe Lin
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  3. David Harwood
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  4. Larry Davis
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Editor information

Rainer Stiefelhagen Rachel Bowers Jonathan Fiscus

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© 2008 Springer-Verlag Berlin Heidelberg

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Tran, S., Lin, Z., Harwood, D., Davis, L. (2008). UMD_VDT, an Integration of Detection and Tracking Methods for Multiple Human Tracking. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_15

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  • DOI: https://doi.org/10.1007/978-3-540-68585-2_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68584-5

  • Online ISBN: 978-3-540-68585-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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