Title :
Automatic facial expression recognition for image sequences
Author :
Sarawagi, Varsha ; Arya, K.V.
Author_Institution :
AIM & ACT Dept., Banasthali Vidyapith, Vanasthali, India
Abstract :
A human face has a distinct and unique characteristics which make it play a very critical role in recognizing facial expression in a “facial expression recognition system.” Identifying or as we say it detection of expressions plays a big and significant role in a facial expression recognition system. If we talk about a human being it becomes an easy task recognize expression in any particular image sequence, but at the same time if we talk about fully automated systems not many are currently available or capable to do so. The field of facial expression recognition do have many different applications and its importance, it might be used to have an interaction between a human being and a computer, here a user, without using his hands, can give commands or instruct to the computer system with the help of facial expression recognition system. Quite a few options are available to identify a face in an image in an efficient and accurate manner, although similar cannot be said for features detection in a video sequence frame. Most systems are still dependent on manual operations for same. Here in this paper we have emphasizes on color normalization and facial feature extraction which uses LBP (Local Binary Pattern) as an effective feature detection approach, where the existing algorithms have been modified to improve the facial expression recognition accuracy. The recognition accuracy on the Indian database is observe to be 94.7%.
Keywords :
emotion recognition; face recognition; feature extraction; image sequences; Indian database; LBP; color normalization; expression detection; face identification; facial expression recognition system; facial feature extraction; feature detection approach; image sequence; local binary pattern; Accuracy; Eyebrows; Face; Face recognition; Feature extraction; Image recognition; Lips; Active State Method; Feature Selection; Local Binary Pattern; Support Vector Machine; Vertical Time Backward;
Conference_Titel :
Contemporary Computing (IC3), 2013 Sixth International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-0190-6
DOI :
10.1109/IC3.2013.6612205