Abstract
We present a facial expression recognition algorithm in this paper, which is based on a combination of the Gabor Feature and the Sprase Representation based Classification(SRC). First, improved Gabor filter is used to extract features. Then we use Principle Component Analysis (PCA) to reduce the dimension of Gabor feature to avoid redundancy. Finally, SRC is used to recognize and classify facial expression. Experiments on facial expression database JAFFE and Cohn-Kanade show that our approach is effective for both dimension reduction and recognition performance. The proposed method achieve 97.68% recognition accuracy on JAFFE.
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Lu, X., Kong, L., Liu, M., Zhang, X. (2015). Facial Expression Recognition Based on Gabor Feature and SRC. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_49
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DOI: https://doi.org/10.1007/978-3-319-25417-3_49
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