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Proceedings Paper

Facial expression recognition using joint multi-resolution multi-area ULBP representation
Author(s): Xiaoyan Dang; Anbang Yao; Wei Wang; Zhang Ya; Zhihua Wang; Zhuo Wang
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Paper 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.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754615 (26 February 2010); doi: 10.1117/12.852739
Show Author Affiliations
Xiaoyan Dang, Intel China Research Ctr. (China)
Anbang Yao, Intel China Research Ctr. (China)
Wei Wang, Intel China Research Ctr. (China)
Zhang Ya, Intel China Research Ctr. (China)
Zhihua Wang, Intel China Research Ctr. (China)
Zhuo Wang, Intel China Research Ctr. (China)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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