Facial expression recognition using joint multi-resolution multi-area ULBP representation

26 February 2010 Facial expression recognition using joint multi-resolution multi-area ULBP representation

Xiaoyan Dang, Anbang Yao, Wei Wang, Zhang Ya, Zhihua Wang, Zhuo Wang

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Proceedings Volume 7546, Second International Conference on Digital Image Processing; 754615 (2010) https://doi.org/10.1117/12.852739
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

Abstract

In this paper, we propose a robust multi-layer texture representation for facial expressions. Our representation is built up using multi-resolution (MR) uniform local binary pattern (ULBP) features on multi-areas (MA) in facial image. Experiments show that this multi-resolution and multi-area (MRMA) strategy could both greatly improve the discriminative ability of texture representation. Based on the proposed MRMA ULBP representation for facial expression, we propose a MRMA ULBP representation + SVM classifier facial expression recognition system. Experiments based on 21 trained one-against-one SVM classifiers show average recognition accuracy of 92.59% on JAFFE database.

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Xiaoyan Dang, Anbang Yao, Wei Wang, Zhang Ya, Zhihua Wang, and Zhuo Wang "Facial expression recognition using joint multi-resolution multi-area ULBP representation", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754615 (26 February 2010); https://doi.org/10.1117/12.852739

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