Facial expression recognition using neural network of congener learning
类间学习神经网络的人脸表情识别*

In view of the current unrelated status of expressions recognition in congener information, this paper proposed an algorithm of the neural network classification of expression congener learning. The algorithm first built a pair of network of BP and an unit of the distance judgment evidence which was only used to calculate the actual distance between categories, and the congener expected distance was obtained under a lot of experiments, then amended the network by the actual output of inner class and the expected distance of congener, finally tested expression recognition through a set of samples. The experimental results demonstrate the feasibility of the algorithm which is able to link information between two expressions at random closely. It shows that the algorithm can improve the efficiency and accuracy of facial expression recognition obviously.