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Feature space-based human face image representation and recognition
Opt. Eng. 51, 017205 (Feb 07, 2012); http://dx.doi.org/10.1117/1.OE.51.1.017205
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Add to FacebookWe propose a novel face recognition method that represents and classifies face images in the feature space. It first assumes that in the feature space the test sample can be well expressed by a linear combination of the training samples, and then it exploits the obtained linear combination to perform face recognition. We also present the foundation, rationale, and characteristics of, as well as the differences between, our method and conventional kernel methods. The analysis shows that our method is a representation-based kernel method and works in the feature space. This method might be able to outperform the representation-based methods that work in the original space. The experimental results show that our method partially possesses the properties of “sparseness” and is able to reduce greatly the effects of noise and occlusion in the test sample.
© 2012 Society of Photo-Optical Instrumentation Engineers
History
Received Jul 05, 2011
Accepted Nov 15, 2011
Revised Oct 18, 2011
Published online Feb 07, 2012
Accepted Nov 15, 2011
Revised Oct 18, 2011
Published online Feb 07, 2012
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Yong Xu, Zizhu Fan and Qi Zhu, "Feature space-based human face image representation and recognition",
Opt. Eng. 51, 017205 (Feb 07, 2012); http://dx.doi.org/10.1117/1.OE.51.1.017205
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