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)


    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
    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 → …


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


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