Improve the Recognition Rate of Facial Expressions by Normalized Facial Features of Different Personal Face and Photo Sizes
Shih‐Lin Wu, Jun-Wei Hsu · 2015
With the advancement in camera techniques, the recognition of human facial expressions has become an important research topic in recent years. Most of the face recognition systems are trying to seek facial features such as eyes and mouth automatically. But the results are inefficient because of the wrong angle and size of a face compared with facial database. In this paper, we propose a real time facial expression recognition system which possesses two functions. First, the system extracts facial features from human face and rotates to the right angle if the face did not pose the right angle. Second, to solve the different face sizes caused by near-far distance to the camera, the system employs a normalization method based on the fixed length of some features on user faces. From experimental results, the system can identify the facial expressions with a high precision rate.