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论文类型：期刊论文

发表时间：2010-09-01

发表刊物：INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY

收录刊物：SCIE、EI、Scopus

卷号：20

期号：3

页面范围：253-260

ISSN号：0899-9457

关键字：PPBTF; adaboost; Gabor; SVM

摘要：PCA, ICA, and Gabor wavelet are considered as the important and powerful face representation methods. In this article, we propose a new approach for face representation, which is called a pixel-pattern-based texture feature (PPBTF) and apply it to the real-time facial expression recognition. A gray scale image is transformed into a pattern map where edges and lines are used for characterizing the facial texture information. Based on the pattern map, a feature vector is comprised of the numbers of the pixels belonging to each pattern. We use the image basis functions obtained by principal component analysis as the templates for pattern matching. Adaboost and Support Vector Machine are adopted to classify facial expression. Extensive experiments on the Cohn-Kanade Database, PIE Database, and DUT Database illustrate that the PPBTF is quite effective and insensitive to illumination. The comparison with Gabor show the PPBTF is speedy. (C) 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 253-260, 2010; View this article online at wileyonlinelibrary.com. DOI 10.1002/ima.20245