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  • A Comparative Evaluation of Average Face on Holistic and Local Face Recognition Approaches

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    Author(s)
    Zhao, S
    Zhang, X
    Gao, Y
    Griffith University Author(s)
    Gao, Yongsheng
    Year published
    2008
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    Abstract
    This study focuses on a recent paper "100% Accuracy in Automatic Face Recognition" published on Science, in which an "Average Face" is proposed and claimed to be capable of dramatically improving performance of a face recognition system. To reveal its working mechanism, we perform the averaging process using pose-varied synthetic images generated from 3D face database and conduct a comparative study to observe its effectiveness on holistic and local face recognition approaches. Two representative methods, i.e. Eigenface and Local Binary Pattern (LBP) are employed to perform the experiments. It is interesting to find from our ...
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    This study focuses on a recent paper "100% Accuracy in Automatic Face Recognition" published on Science, in which an "Average Face" is proposed and claimed to be capable of dramatically improving performance of a face recognition system. To reveal its working mechanism, we perform the averaging process using pose-varied synthetic images generated from 3D face database and conduct a comparative study to observe its effectiveness on holistic and local face recognition approaches. Two representative methods, i.e. Eigenface and Local Binary Pattern (LBP) are employed to perform the experiments. It is interesting to find from our experiments that the performance of the "Average Face" is not independent of the face recognition approaches. Although face averaging increases the recognition accuracy of Eigenface method, it impairs the performance of LBP method.
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    Conference Title
    Proceedings - International Conference on Pattern Recognition
    Publisher URI
    http://ieeexplore.ieee.org/servlet/opac?punumber=4740202
    DOI
    https://doi.org/10.1109/ICPR.2008.4761430
    Copyright Statement
    © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Publication URI
    http://hdl.handle.net/10072/22905
    Collection
    • Conference outputs

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