DocumentCode :
3251416
Title :
Hierarchical clustering based facial expression analysis from video sequence
Author :
Mitra, Soma ; Saha, Chandrani ; Das, Apurba
Author_Institution :
Centre for Dev. of Adv. Comput. (CDAC), Kolkata, India
fYear :
2011
fDate :
26-28 Dec. 2011
Firstpage :
1
Lastpage :
5
Abstract :
Facial expression analysis from video sequences has been an active research area from the last two decades. There are plenty of algorithms for classification of six prototypic facial expressions from video sequences. In present paper we have proposed a novel method of hierarchical clustering for classification of facial expressions. The optical flow algorithm is used for detection of muscle movement arises due to different expressions. The maximally deformed facial regions (RoI) are extracted. Statistical features in these RoI are utilized for classification. The hierarchical Fuzzy C-Means algorithm classifies the six basic prototypic expression.
Keywords :
face recognition; fuzzy set theory; image sequences; muscle; pattern clustering; statistical analysis; video signal processing; facial expression analysis; hierarchical clustering; hierarchical fuzzy C-means algorithm; muscle movement detection; optical flow algorithm; statistical feature; video sequence; Computer vision; Face; Face recognition; Feature extraction; Image motion analysis; Optical imaging; Vectors; Fuzzy C-means (FCM); hierarchical clustering; kurtosis; optical flow; skew-ness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication and Industrial Application (ICCIA), 2011 International Conference on
Conference_Location :
Kolkata, West Bengal
Print_ISBN :
978-1-4577-1915-8
Type :
conf
DOI :
10.1109/ICCIndA.2011.6146667
Filename :
6146667
Link To Document :
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