DocumentCode :
2004556
Title :
Recognizing facial expressions: Computational models and humans
Author :
Shenoy, Aruna ; Davey, Neil ; Frank, Raphael
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
fYear :
2013
fDate :
9-11 Sept. 2013
Firstpage :
191
Lastpage :
198
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. There have been a limited number of studies comparing the performance of human subjects with computational models for facial expression recognition. This paper does a genuine attempt in making this comparison.
Keywords :
emotion recognition; face recognition; biologically plausible computational models; facial expression identification; human facial expression analysis; human facial expression recognition; social interactions; Computational modeling; Correlation; Face; Filter banks; Gabor filters; Principal component analysis; Support vector machines; Curvilinear Component Analysis; Facial expression; Gabor filters; Principal component analysis; Support Vector machines; human subjects;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence (UKCI), 2013 13th UK Workshop on
Conference_Location :
Guildford
Print_ISBN :
978-1-4799-1566-8
Type :
conf
DOI :
10.1109/UKCI.2013.6651305
Filename :
6651305
Link To Document :
بازگشت