Face recognition from sequences using models of identity

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

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    A method for modelling and recognising facial identity is described within the context of an integrated system for face recognition in dynamic scenes. Recognition is based sequences rather than isolated images. Mixture models provide estimates of class-conditional probabilities and these are used to accumulate recognition confidence over time. Results are presented using data from the integrated system
    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
    Pages507-514
    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., & Gong, S. (1998). Face recognition from sequences using models of identity. 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. 507-514 ). (Lecture notes in computer science; Vol. 1351). Springer . https://doi.org/10.1007/3-540-63930-6_161