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Proceedings Paper

Combining appearance and geometric features for facial expression recognition
Author(s): Hui Yu; Honghai Liu
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Paper Abstract

This paper introduces a method for facial expression recognition combining appearance and geometric facial features. The proposed framework consistently combines multiple facial representations at both global and local levels. First, covariance descriptors are computed to represent regional features combining various feature information with a low dimensionality. Then geometric features are detected to provide a general facial movement description of the facial expression. These appearance and geometric features are combined to form a vector representation of the facial expression. The proposed method is tested on the CK+ database and shows encouraging performance.

Paper Details

Date Published: 4 March 2015
PDF: 6 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 944308 (4 March 2015); doi: 10.1117/12.2179066
Show Author Affiliations
Hui Yu, Univ. of Portsmouth (United Kingdom)
Honghai Liu, Univ. of Portsmouth (United Kingdom)


Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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