Modeling the effect of motion at encoding and retrieval for same and other race face recognition

Hui Fang, Nicholas Costen, Natalie Butcher, Karen Lander

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    We assess the role of motion when encoding and recognizing unfamiliar faces, using a recognition memory paradigm. This reveals a facilitative role for non-rigid motion when learning unfamiliar same and other-race faces, and indicate that it is more important that the face is learned, rather than recognized, in motion. A computational study of the faces using Appearance Models of facial variation, shows that this lack a motion effect at recognition was reproduced by a norm-based encoding of faces, with the selection of features based on distance from the norm.
    Original languageEnglish
    Title of host publicationCognitive behavioural systems
    Subtitle of host publicationCOST 2102 International Training School, Dresden, Germany, February 21-26, 2011, revised selected papers
    EditorsAnna Esposito, Antonietta M. Esposito, Alessandro Vinciarelli, Rüdiger Hoffmann, Vincent C. Müller
    Place of PublicationHeidelberg, Dordrecht, London, New York
    PublisherSpringer Nature
    Pages184-190
    Number of pages7
    Volume7403
    ISBN (Electronic)9783642345845
    ISBN (Print)9783642345838
    DOIs
    Publication statusPublished - 2012

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Volume7403
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Keywords

    • Face Recognition
    • Facial Motion
    • Active Appearance Model
    • Facial Variation
    • Recognition Memory Paradigm

    Fingerprint

    Dive into the research topics of 'Modeling the effect of motion at encoding and retrieval for same and other race face recognition'. Together they form a unique fingerprint.

    Cite this