计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (18): 201-203.

• 图形、图像、模式识别 • 上一篇    下一篇

基于PCA算法的人脸识别

焦斌亮,陈 爽   

  1. 燕山大学 信息工程学院 电子工程系,河北 秦皇岛 066004
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-06-21 发布日期:2011-06-21

Face recognition based on PCA

JIAO Binliang,CHEN Shuang   

  1. Department of Electronic Engineering,College of Information Engineering,Yanshan University,Qinhuangdao,Hebei 066004,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-06-21 Published:2011-06-21

摘要: 介绍了隐马尔可夫特征脸模型(HMEM),由概率性主成分分析方法(PPCA)与离散空间马尔可夫模型法(SL-HMM)整合而成,具有PPCA和SL-HMM的双重特性。利用ORL数据库进行人脸识别实验,结果说明该模型在性能上表现出较大的优势。

关键词: 人脸识别, 特征脸, 概率主成分分析, 隐马尔可夫模型

Abstract: This paper introduces the Hidden Markov Eigenface Model(HMEM) in which the Probabilistic Principal Component Analysis(PPCA) is integrated into Separable Lattice Hidden Markov Models(SL-HMM),and the proposed model has good properties of both PPCA and SL-HMM.The face recognition experiments based on the ORL database show that the proposed model improves the performance signicantly.

Key words: face recognition, eigenface, Probabilistic Principal Component Analysis(PPCA), Hidden Markov Models(HMM)