Feature space-based human face image representation and recognition

Yong Xu; Zizhu Fan; Qi Zhu

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Feature space-based human face image representation and recognition

机译：Feature space-based human face image representation and recognition

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摘要

We 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.

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来源
《Optical Engineering》 |2012年第1期|017205-1-017205-7|共7页
作者
Yong Xu; Zizhu Fan; Qi Zhu;
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作者单位

Harbin Institute of Technology, Bio-computing Research Center, Shenzhen Graduate School and Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China;

Harbin Institute of Technology, Bio-computing Research Center, Shenzhen Graduate School, Shenzhen, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
image representation; classification; computer vision;

Feature space-based human face image representation and recognition

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