A Two-Phase Test Sample Sparse Representation Method for Use With Face Recognition

In this paper, we propose a two-phase test sample representation method for face recognition. The first phase of the proposed method seeks to represent the test sample as a linear combination of all the training samples and exploits the representation ability of each training sample to determine M &...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology Jg. 21; H. 9; S. 1255 - 1262
Hauptverfasser:	Yong Xu, Zhang, D., Jian Yang, Jing-Yu Yang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.09.2011 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Artificial intelligence Circuits Classification Computer science; control theory; systems Computer vision Electronic mail Exact sciences and technology Face recognition Image processing Information, signal and communications theory Materials Nearest neighbor searches Pattern recognition Pattern recognition. Digital image processing. Computational geometry Principal component analysis Representations Signal processing sparse representation Studies Telecommunications and information theory Training transform methods Transforms Learning Biometrics Nearest neighbour Computer vision transform methods Linear combination Face recognition Image processing Test method Sparse representation Pattern recognition Automatic recognition
ISSN:	1051-8215, 1558-2205
Online-Zugang:	Volltext
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