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    Recognising faces in unseen modes: a tensor based approach

    Access Status
    Fulltext not available
    Authors
    Rana, Santu
    Liu, Wan-Quan
    Lazarescu, Mihai
    Venkatesh, Svetha
    Date
    2008
    Type
    Conference Paper
    
    Metadata
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    Citation
    Rana, S. and Liu, W. and Lazarescu, M. and Venkatesh, S. 2008. Recognising faces in unseen modes: a tensor based approach, in IEEE Conference on Computer Vision and Pattern recognition, Jun 23-28 2008. Anchorage, Alaska: IEEE.
    Source Title
    IEEE Computer Society conference on computer vision and pattern recognition
    Source Conference
    26th IEEE conference on computer vision and pattern recognition
    DOI
    10.1109/CVPR.2008.4587813
    ISBN
    9781424422432
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/6414
    Collection
    • Curtin Research Publications
    Abstract

    This paper addresses the limitation of current multilinear techniques (multilinear PCA, multilinear ICA) when applied to face recognition for handling faces in unseen illumination and viewpoints. We propose a new recognition method, exploiting the interaction of all the subspaces resulting from multilinear decomposition (for both multilinear PCA and ICA), to produce a new basis called multilinear-eigenmodes. This basis offers the flexibility to handle face images at unseen illumination or viewpoints. Experiments on benchmarked datasets yield superior performance in terms of both accuracy and computational cost.

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