Automatic multi-head detection and tracking system using a novel detection-based particle filter and data fusion

Wei Qu, Nidhal Bouaynaya, Dan Schonfeld

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Scopus citations

    Abstract

    We present a novel automatic system integrating head detection with particle filter for realtime multi-head tracking (MHT) in video. Distinct with the conventional particle filter which gets particles from the prior density, we propose a novel importance function based on the up to date detection and motion observation which makes the particles more effective and helps us to achieve stable tracking by using much less particles. We also propose a general likelihood model in the context of MHT. Different information can be fused in a principle manner to make the tracker more stable. The proposed approach can handle not only the changes of scale, lighting, zooming, and pose, but also fast motion, appearance, and hard multi-head occlusion.

    Original languageEnglish (US)
    Title of host publication2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Proceedings - Image and Multidimensional Signal Processing Multimedia Signal Processing
    PagesII661-II664
    DOIs
    StatePublished - 2005
    Event2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 - Philadelphia, PA, United States
    Duration: Mar 18 2005Mar 23 2005

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    VolumeII
    ISSN (Print)1520-6149

    Other

    Other2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
    CountryUnited States
    CityPhiladelphia, PA
    Period3/18/053/23/05

    All Science Journal Classification (ASJC) codes

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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