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  • Random Gabor based templates for facial expression recognition in images with facial occlusion

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    Tjondronegoro224536-Accepted.pdf (1.290Mb)
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    Accepted Manuscript (AM)
    Author(s)
    Zhang, Ligang
    Tjondronegoro, Dian
    Chandran, Vinod
    Griffith University Author(s)
    Tjondronegoro, Dian W.
    Chandran, Vinod
    Year published
    2014
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    Abstract
    Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of texture features in local facial regions and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates ...
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    Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of texture features in local facial regions and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. Results on the parameter sensitivity experiments demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusion ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.
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    Journal Title
    Neurocomputing
    Volume
    145
    DOI
    https://doi.org/10.1016/j.neucom.2014.05.008
    Copyright Statement
    © 2014 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Information and computing sciences
    Engineering
    Psychology
    Science & Technology
    Computer Science, Artificial Intelligence
    Computer Science
    Facial expression recognition
    Publication URI
    http://hdl.handle.net/10072/390252
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    • Journal articles

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