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  • Combined Classification of Multiple Views using Facial Corners

    Author(s)
    Gao, YS
    Leung, MKH
    Griffith University Author(s)
    Gao, Yongsheng
    Year published
    2002
    Metadata
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    Abstract
    The profile view of a face provides a complementary structure that is not seen in the frontal view. The classification system combining both frontal and profile views of faces can improve the classification accuracy. And it would be more foolproof because it is difficult to fool the profile face identification by a mask. This paper proposes a new face recognition approach, which can be applied on both frontal and profile faces, to build a robust combined multiple view face identification system. The recognition employs a novel facial corner coding and matching method, and integrates the outline and interior facial parts in ...
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    The profile view of a face provides a complementary structure that is not seen in the frontal view. The classification system combining both frontal and profile views of faces can improve the classification accuracy. And it would be more foolproof because it is difficult to fool the profile face identification by a mask. This paper proposes a new face recognition approach, which can be applied on both frontal and profile faces, to build a robust combined multiple view face identification system. The recognition employs a novel facial corner coding and matching method, and integrates the outline and interior facial parts in the profile matching. The proposed multiview modified Hausdorff distance fuses multiple views of faces to achieve an improved system performance.
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    Journal Title
    International Journal of Pattern Recognition and Artificial Intelligence
    Volume
    16
    Issue
    5
    DOI
    https://doi.org/10.1142/S021800140200185X
    Subject
    Cognitive and computational psychology
    Publication URI
    http://hdl.handle.net/10072/21564
    Collection
    • Journal articles

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