DocumentCode :
652701
Title :
Analyses of the Differences between Posed and Spontaneous Facial Expressions
Author :
Menghua He ; Shangfei Wang ; Zhilei Liu ; Xiaoping Chen
Author_Institution :
Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2013
fDate :
2-5 Sept. 2013
Firstpage :
79
Lastpage :
84
Abstract :
This paper presents comprehensive analyses of the differences between posed and spontaneous expressions from visible images. First, geometric and appearance features are extracted from the difference images between apex and onset facial images. Secondly, the differences between the posed and spontaneous facial expressions are analyzed through hypothetical testing methods from three aspects: on overall samples, on samples with different genders, and on samples with different expressions. Thirdly, Bayesian networks (BNs) are used to classify posed versus spontaneous expressions from the same three aspects. Statistical analyses on the NVIE database demonstrate the importance of the geometric and appearance features for discriminating posed and spontaneous expressions. Gender effect exists on the differences between posed and spontaneous expressions. It is easier to distinguish posed happiness from spontaneous happiness than other expressions. Recognition experimental results confirm the observations of statistical analyses in most cases.
Keywords :
belief networks; face recognition; feature extraction; statistical analysis; visual databases; Bayesian networks; NVIE database; apex; feature extraction; onset facial images; posed facial expressions; spontaneous facial expressions; statistical analyses; visible images; Bayes methods; Databases; Face recognition; Feature extraction; Mouth; Statistical analysis; Testing; Bayesian Network; posed versus spontaneous expression; statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on
Conference_Location :
Geneva
ISSN :
2156-8103
Type :
conf
DOI :
10.1109/ACII.2013.20
Filename :
6681411
Link To Document :
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