Video-Based Facial Expression Recognition Using Hough Forest

This paper introduces a new video-based facial expression recognition system. Facial expression analysis encounters two major problems: non-rigid shape deformation and person-specific facial expression appearance. Our method analyzes the video sequence to recognize facial expression and locate the temporal apex of the facial expression by using modified Hough forest and minimizing the influence of person-specific facial expression appearance. Our contributions are (1) random sampling 3-D accumulated spatial-temporal motion map to generate video patches, (2) proposing the correlation filtering for more effective Hough voting, and (3) recognizing and locating the apex of the facial expression. The experimental results show that the performance of our method is better than the other face expression recognition methods.