Object tracking using adaptive colour mixture models

Stephen J. McKenna (Lead / Corresponding author), Yogesh Raja (Lead / Corresponding author), Shaogang Gong (Lead / Corresponding author)

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

    24 Citations (Scopus)

    Abstract

    The use of adaptive Gaussian mixtures to model the colour distributions of objects is described. These models are used to perform robust, real-time tracking under varying illumination, viewing geometry and camera parameters. Observed log-likelihood measurements were used to perform selective adaptation.
    Original languageEnglish
    Title of host publicationComputer Vision — ACCV'98
    Subtitle of host publicationThird Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings
    EditorsRoland Chin, Ting-Chuen Pong
    Place of PublicationBerlin
    PublisherSpringer
    Pages615-622
    Number of pages8
    Volume1
    ISBN (Electronic)9783540696698
    ISBN (Print)9783540639305
    DOIs
    Publication statusPublished - 1998
    Event3rd Asian Conference on Computer Vision - Hong Kong University of Science & Technology (HKUST), Hong Kong, Hong Kong
    Duration: 8 Jan 199810 Jan 1998
    http://www.cse.ust.hk/accv98/

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Volume1351
    ISSN (Print)0302-9743

    Conference

    Conference3rd Asian Conference on Computer Vision
    Abbreviated titleACCV'98
    CountryHong Kong
    CityHong Kong
    Period8/01/9810/01/98
    Internet address

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  • Cite this

    McKenna, S. J., Raja, Y., & Gong, S. (1998). Object tracking using adaptive colour mixture models. In R. Chin, & T-C. Pong (Eds.), Computer Vision — ACCV'98: Third Asian Conference on Computer Vision Hong Kong, China, January 8–10, 1998 Proceedings (Vol. 1, pp. 615-622). (Lecture notes in computer science; Vol. 1351). Springer . https://doi.org/10.1007/3-540-63930-6_174