Facial Expression Recognition Algorithm Based on Reverse Co-Salient Regions (RCSR) Features

To solve the problems of absence of expression-correlation in single-image-based expression recognition, and limitation of one classifier, a novel facial expression recognition method based on reverse co-saliency region features is proposed in this paper. Firstly, seven different classifications of expression images of a same person are used to extract facial changed regions of different expressions by a reverse co-saliency features method, named Reverse Co–Salient Regions (RCSR). Secondly, the extracted salient regions are described as texture and shape features LBP and HOG. Finally, based on RCSR features, multi-classifiers decision mechanism is used for expressions recognition. The following experimental results show that the recognition accuracy increases obviously compared with 3 different kinds of single-image-based expression recognition methods.