Face Recognition Based Hybrid Fuzzy Hidden Markov Models

摘要：

This paper proposes Hybrid Fuzzy Hidden Markov Models (FHMM) for face recognition. This recognition system includes fuzzy integral theory and Hidden Markov Model. Applying fuzzy expectation-maximization (FEM) algorithm in the Hidden Markov Model (HMM) is to estimate the relative parameters of faces which are close to real values in a better condition Besides, in order to precisely obtain the probability density function of observations vector, taking full use of Gaussian Mixture Models (GMM), in which the weights are designed by using the fuzzy c-means (FCM) function. Comparing to conventional HMM, the proposed method achieves a better result.

关键词： Face Recognition Hidden Markov Model EM Algorithm FEM AlgorUhm GMM

作者: Chaocheng Xie Lei Li Haixu Wang Jiao He

作者单位: School of Electronic Engineering, University of Electronic Science and Technology of China Cheng Du, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1501-1505

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）