Facial Expression Recognition in Video Sequence Images by Using Optical Flow
In this paper a new method for facial expression recognition is presented. According to this algorithm, an appropriate mask is designed using Gabor filters, and it is convolved with first frame of video sequence images. Then oval part of face is specified and its main components are characterized. By using Lucas Kanade method for optical flow analysis to determine the motion flow vectors on the regions of main parts during frames largest, motion vectors related to sensitive points of face are extracted and classified to the six basic classes such as: normality, happiness, sadness, anger. disgust, and surprise, facial expression are extracted. This method has high accuracy in comparison with other methods and dont need for select landmark manually at first.
component facial expression gabor fiker optical flow
Behnam Kabirian Dehkordi Javad Haddadnia
Tarbiat Moallem university of Sabzevar Sabzevar-IRAN
国际会议
2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)
大连
英文
727-730
2010-07-05（万方平台首次上网日期，不代表论文的发表时间）