Facial Expression Recognition Based on Multi-Channel Fusion of Gabor Features

Abstract:

This paper presents a facial expression recognition algorithm based on multi-channel integration of Gabor feature. First, a Gabor wavelet filter extracts facial features with 5 scales and 8 orientations, and then transform the 40 channels into 13 channels according to the maximum rule presented in this paper. Second, we reduce the dimension of expression features by the method of PCA+LDA. At last, expression features are classified using the nearest neighbor method. The experiments involve two databases and show that the proposed algorithm can recognize facial expression in high rate.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 1963-1967
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.1963
• Online since: September 2013
• Authors: Shu Yi Wang*, Jing Ling Wang, Chuan Zhen Li
• Keywords: Expression Recognition, Gabor Transform, Latent Dirichlet Allocation (LDA), Multi-Channel Fusion, Multi-Scale, PCA

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