DocumentCode :
594901
Title :
Posed and spontaneous expression distinguishment from infrared thermal images
Author :
Zhilei Liu ; Shangfei Wang
Author_Institution :
Key Lab. of Comput. & Communicating Software of AnHui Province, Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
1108
Lastpage :
1111
Abstract :
In this paper, we try to distinguish between the posed and spontaneous facial expressions through infrared thermal images. Firstly, six statistical features are extracted from the temperature difference matrices between the apex and onset facial expression frames in each facial subregion. Secondly, the thermal differences between the posed facial expressions and spontaneous ones are analyzed by a Paired-Samples T-test. Thirdly, Bayesian Networks are adopted to classify posed and spontaneous expressions based on these temperature statistical features. Experimental results on the thermal subdatabase of the USTC-NIVE demonstrate the feasibility and effectiveness of posed and spontaneous expression recognition through facial temperature changes. This study also illustrates that the importance of different facial subregions´ temperature variances for differentiating different kinds of posed and spontaneous expressions.
Keywords :
belief networks; face recognition; feature extraction; image classification; infrared imaging; statistical testing; visual databases; Bayesian networks; USTC-NIVE thermal subdatabase; apex facial expression frames; facial subregion; facial temperature changes; infrared thermal images; onset facial expression frames; paired-samples T-test; posed expression classification; posed expression recognition; posed facial expressions; spontaneous expression classification; spontaneous expression recognition; spontaneous facial expressions; temperature difference matrices; temperature statistical feature extraction; temperature variances; thermal differences; Conferences; Databases; Face recognition; Feature extraction; Forehead; Temperature distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460330
Link To Document :
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