Face recognition using multiple facial features

被引：9

作者：

Rajagopalan, A. N. ^{[1
]}

Rao, K. Srinivasa ^{[1
]}

Kumar, Y. Anoop ^{[1
]}

机构：

[1] Indian Inst Technol, Image Proc & Comp Vis Lab, Dept Elect Engn, Madras 600036, Tamil Nadu, India

来源：

PATTERN RECOGNITION LETTERS | 2007年 / 28卷 / 03期

关键词：

face recon-ition; principal components analysis; Fisher's linear discriminant; block histogram modification; edginess image; distance in feature space; fusion;

D O I：

10.1016/j.patrec.2006.04.003

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 a face recognition method that fuses information acquired from global and local features of the face for improving performance. Principle components analysis followed by Fisher analysis is used for dimensionality reduction and construction of individual feature spaces. Recognition is done by probabilistically fusing the confidence weights derived from each feature space. The performance of the method is validated on FERET and AR databases. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：335 / 341

页数：7

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