Distortion-invariant (Pose and illumination) face recognition using new SVM

被引：1

作者：

Casasent, D ^{[1
]}

Yuan, C ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Dept ECE, Pittsburgh, PA 15213 USA

来源：

INTELLIGENT ROBOTS AND COMPUTER VISION XXII: ALGORITHMS, TECHNIQUES, AND ACTIVE VISION | 2004年 / 5608卷

关键词：

face recognition; face verification; pose estimation; support vector machine;

D O I：

10.1117/12.580132

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Face recognition with both pose and illumination variations is considered. In addition, we consider the ability of the classifier to reject non-member or imposter face inputs; most prior work has not addressed this. Initially, non-registered test and training set imagery is used (this is realistic) and a two-step pose estimation/face recognition processor is employed which includes registration of the test input to the reference poses. A new SVRDM support vector representation and discrimination machine classifier is proposed and initial face recognition-rejection results are presented. Face recognition and verification results are presented.

引用

页码：1 / 12

页数：12

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