用隐马尔可夫模型设计人脸表情识别系统

根据隐马尔可夫模型(HMM)的基本理论和算法设计了一个人脸表情识别系统。该系统由两层HMM组成:低层由六个HMM组成,分别对应六种特定表情。人脸表情特征向量进入系统后,经过低层HMM初步识别,其结果组成高层HMM的观察向量,经过高层HMM解码,确认出表情,从而提高了系统的识别率,增强了系统的健壮性。

Design of Recognition for Facial Expression by Hidden Markov Model

Hidden Markov Model(HMM) is a widely used statistical model.This paper deal with the design of a recognition system for facial expression in the light of the principal theory and algorithm of the HMM.The system consists of two levels of HMM,with the low level composed of six HMM,corresponding to six expression-specific.The vectors of the facial expression features,after put into the system,is primarily identified through the low HMMsand result in the observation vectors of the high level of the HMM.Through deciphering of the HMM,the expression are identified,thus enhancing the recognition rate and strengthening the system to a higher level.