FACE RECOGNITION - FEATURES VERSUS TEMPLATES

被引：1319

作者：

BRUNELLI, R

POGGIO, T

机构：

[1] MIT, ARTIFICIAL INTELLIGENCE LAB, CAMBRIDGE, MA 02139 USA

[2] MIT, DEPT BRAIN & COGNIT SCI, CAMBRIDGE, MA 02139 USA

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1993年 / 15卷 / 10期

关键词：

CLASSIFICATION; FACE RECOGNITION; KARHUNEN-LOEVE EXPANSION; TEMPLATE MATCHING;

D O I：

10.1109/34.254061

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Over the last 20 years, several different techniques have been proposed for computer recognition of human faces. The purpose of this paper is to compare two simple but general strategies on a common database (frontal images of faces of 47 people: 26 males and 21 females, four images per person). We have developed and implemented two new algorithms; the first one is based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second one is based on almost-grey-level template matching. The results obtained on the testing sets (about 90% correct recognition using geometrical features and perfect recognition using template matching) favor our implementation of the template-matching approach.

引用

页码：1042 / 1052

页数：11