DocumentCode :
2173949
Title :
Biologically plausible computational models for facial expression recognition
Author :
Shenoy, Aruna ; Davey, Neil ; Frank, Raphael
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
fYear :
2013
fDate :
17-18 Sept. 2013
Firstpage :
39
Lastpage :
44
Abstract :
This paper discusses various biologically plausible computational models that recognize human facial expression and analyze them. Identifying facial expressions is a non trivial task for a human and is a key part of social interactions. However, it is not as simple as that for a computational system. Here we analyze six different universally accepted facial expressions for analysis with the aid of six biologically plausible computational models.
Keywords :
emotion recognition; face recognition; biologically plausible computational models; facial expression recognition; social interactions; Accuracy; Computational modeling; Educational institutions; Face; Gabor filters; Principal component analysis; Support vector machines; Curvilinear Component Analysis; Gabor filters; Principal Component Analysis; Support Vector Machines; facial expressions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Electronic Engineering Conference (CEEC), 2013 5th
Conference_Location :
Colchester
Type :
conf
DOI :
10.1109/CEEC.2013.6659442
Filename :
6659442
Link To Document :
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