A New Appearance-Based Facial Expression Recognition System with Expression Transition Matrices

In this study, we propose a novel image-based facial expression recognition method called "expression transition" to identify six kinds of facial expressions (anger, fear, happiness, neutral, sadness, and surprise) at low-resolution images. The boosted tree classifiers and template matching are used to locate and crop the effective face region that may characterize the facial expressions. Then, the expression transformed images via a set of expression transition matrices are matched with the real facial images to identify the facial expressions. The proposed system can recognize the facial expressions with the speed of 0.24 seconds per frame and accuracy. above 86%.