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    A computational other-race-effect analysis for 3D facial expression recognition

    Access Status
    Fulltext not available
    Authors
    Xue, M.
    Duan, X.
    Zhou, J.
    Wang, C.
    Wang, Y.
    Li, Z.
    Liu, Wan-Quan
    Date
    2016
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Xue, M. and Duan, X. and Zhou, J. and Wang, C. and Wang, Y. and Li, Z. and Liu, W. 2016. A computational other-race-effect analysis for 3D facial expression recognition, in Chinese Conference on Biometric Recognition (CCBR), pp. 483-493.
    Source Title
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    DOI
    10.1007/978-3-319-46654-5_53
    ISBN
    9783319466538
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/37022
    Collection
    • Curtin Research Publications
    Abstract

    © Springer International Publishing AG 2016.This paper investigates the other-race-effects in automatic 3D facial expression recognition, giving the computational analysis of the recognition performance obtained from two races, namely white and east Asian. The 3D face information is represented by local depth feature, and then a feature learning process is used to obtain race-sensitive features to simulate the other-race-effect. The learned features from own race and other race are then used to do facial expression recognition. The proposed analysis is conducted on BU-3DFE database, and the results show that the learned features from one race achieve better recognition performance on the own-race faces. It reveals that the other-race-effect are significant in facial expression recognition problem, which confirms the results of psychological experiment results.

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