Interest-point Based Face Recognition from Range Images

F.R.M. Al-Osaimi, Mohammed Bennamoun, Ajmal Mian

    Research output: Chapter in Book/Conference paperConference paperpeer-review

    4 Citations (Scopus)

    Abstract

    We present a novel approach to interest-point detection tailored to range images. A range image is represented by two images with blob-like patterns that have easily detectable peaks and can be efficiently extracted using convolution kernels. These kernels were designed to produce repeatable and independent blob-like patterns when convolved with the range image. The interest-points correspond to peaks of the patterns after dropping the unstable ones and performing Non-Maximal Suppression (NMS) on their union. The approach was applied to facial range images from the FRGC V2.0 dataset and about 88% repeatability was achieved. Face recognition was also performed by matching the local range regions around the interest-points. An approach based on three levels of matching combined with RAN SAC algorithm was used to increase the correct matches and reduce the false ones. Preliminary recognition results for a database of 466 subjects and 1765 probes were 96.33% identification rate and 90% verification rate at 0.1% False Accept Rate (FAR) for faces under neutral expression.
    Original languageEnglish
    Title of host publicationProceedings of the British Machine Vision Conference 2007
    Place of PublicationU.K.
    PublisherBritish Machine Vision Association
    Pages132-141
    Volume1
    EditionUniversity of Warwick, U.K.
    ISBN (Print)9780902683815
    Publication statusPublished - 2007
    EventInterest-point Based Face Recognition from Range Images - University of Warwick, U.K.
    Duration: 1 Jan 2007 → …

    Conference

    ConferenceInterest-point Based Face Recognition from Range Images
    Period1/01/07 → …

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