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Audio-visual human recognition using semi-supervised spectral learning and hidden Markov models
文献类型:期刊
作者:Feng, Wei[1]  Xie, Lei[2]  Zeng, Jia[3]  Liu, Zhi-Qiang[4]  
机构:[1]City Univ Hong Kong, Sch Creat Media, Media Comp Grp, Hong Kong, Hong Kong, Peoples R China.;
[2]NW Polytech Univ, Sch Comp Sci, Xian 710072, Peoples R China.;
[3]Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China.;
[4]City Univ Hong Kong, Sch Creat Media, Media Comp Grp, Hong Kong, Hong Kong, Peoples R China.;
通讯作者:Feng, W (reprint author), City Univ Hong Kong, Sch Creat Media, Media Comp Grp, Hong Kong, Hong Kong, Peoples R China.
年:2009
期刊名称:JOURNAL OF VISUAL LANGUAGES AND COMPUTING影响因子和分区
卷:20
期:3
页码范围:188-195
增刊:正刊
学科:计算机科学
收录情况:SCI(E)(WOS:000266347300007)  
所属部门:计算机学院
被引频次:4
人气指数:1928
浏览次数:1900
关键词:Face recognition; Speaker identification; Semi-supervised spectral learning; Hidden Markov models (HMMs)
摘要:
This paper presents a multimodal system for reliable human identity recognition under variant conditions. Our system fuses the recognition of face and speech with a general probabilistic framework For face recognition, we propose a new spectral learning algorithm, which considers not only the discriminative relations among the training data but also the generative models for each class. Due to the tedious cost of face labeling in practice, our spectral face learning utilizes a semi-supervised st ...More
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