Independent Component Analysis and Support Vector Machine for face feature extraction

被引：0
|
作者：
Antonini, G [1 ]
Popovici, V [1 ]
Thiran, JP [1 ]
机构：
[1] Swiss Fed Inst Technol, Signal Proc Inst, CH-1015 Lausanne, Switzerland
来源：
AUDIO-AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS | 2003年 / 2688卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection /localization context. The goal is to find a better space where project the data in order to build ten different face-feature classifiers that are robust to illumination variations and bad environment conditions. The method was tested on the BANCA database, in different scenarios: controlled conditions, degraded conditions and adverse conditions.
引用
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页码：111 / 118
页数：8
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