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Expression recognition using fuzzy spatio-temporal modeling
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DOI：10.1016/j.patcog.2007.04.021.png)
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Abstract
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In human-computer interaction, there is a need for computer to recognize human facial expression accurately. This paper proposes a novel and effective approach for facial expression recognition that analyzes a sequence of images (displaying one expression) instead of just one image (which captures the snapshot of an emotion). Fourier transform is employed to extract features to represent an expression. The representation is further processed using the fuzzy C means computation to generate a spatio-temporal model for each expression type. Unknown input expressions are matched to the models using the Hausdorff distance to compute dissimilarity values for classification. The proposed technique has been tested with the CMU expression database, generating superior results as compared to other approaches. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Keywords:
facial expression
Fourier transform
fuzzy C means
HCI
Hausdorff distance
spatio-temporal
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