Region-based face detection

被引:14
|
作者
Ayinde, O
Yang, YH [1 ]
机构
[1] Univ Alberta, Dept Comp Sci, Edmonton, AB T6G 2E8, Canada
[2] SMART Technol Inc, Calgary, AB T2R 1K9, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
correlation; face detection; region-based recognition; symmetry; training;
D O I
10.1016/S0031-3203(01)00196-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Face detection is a challenging task, Several approaches have been proposed for face detection. Some approaches are only good for one face per image, while others can detect multiple faces from an image with greater price to pay in terms of training. In this paper, we present an approach that can be used for single or multiple face detection from simple or cluttered scenes. Faces with different sizes located in any part of an image can be detected using this approach. Three test sets are used to evaluate the system. The system has a detection rate of 100% on test set A containing 200 good quality images (200 faces) with simple backgrounds, Test set B contains 23 images ( 149 faces) with cluttered backgrounds and a mixture of high- and low-quality images. A detection rate of 66.4% is obtained on this set. Test set C is a selection of 22 high-quality images (54 faces) images from different sources including the World Wide Web, and a detection rate of 90.7% is obtained. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:2095 / 2107
页数:13
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