Contourlet structural similarity for facial expression recognition

Lajevardi, S and Hussian, Z 2010, 'Contourlet structural similarity for facial expression recognition', in Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), New York, USA, 11-15 March 2010, pp. 1118-1121.


Document type: Conference Paper
Collection: Conference Papers

Title Contourlet structural similarity for facial expression recognition
Author(s) Lajevardi, S
Hussian, Z
Year 2010
Conference name 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010)
Conference location New York, USA
Conference dates 11-15 March 2010
Proceedings title Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010)
Publisher IEEE
Place of publication New York, USA
Start page 1118
End page 1121
Total pages 4
Abstract This paper presents a novel classification method based on perceptual image quality metrics for facial expression recognition. The features are extracted based on Contourlet sub-bands. Then, the optimum features are selected using minimum redundancy and maximum relevance algorithm (MRMR). The selected features are classified by structural similarity metric in contourlet domain. The proposed method has been extensively assessed using two different databases: the Cohn-Kanade database and the JAFFE database. A series of experiments have been carried out and a comparative study suggests the efficiency of the proposed method in enhancing the classification rates of a number of known algorithms.
Subjects Signal Processing
Keyword(s) Facial expression recognition
Contourlet transform
Structural similarity classification
DOI - identifier 10.1109/ICASSP.2010.5495357
Copyright notice © 2010 IEEE
ISBN 9781424442966
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