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
焦斌亮,陈 爽
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JIAO Binliang,CHEN Shuang
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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)
焦斌亮,陈 爽. 基于PCA算法的人脸识别[J]. 计算机工程与应用, 2011, 47(18): 201-203.
JIAO Binliang,CHEN Shuang. Face recognition based on PCA[J]. Computer Engineering and Applications, 2011, 47(18): 201-203.
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http://cea.ceaj.org/CN/Y2011/V47/I18/201