基于遗传算法重采样人脸样本扩张.pdfVIP

1000-9825/2005/16(06)0000 ©2005 Journal of Software 软 件 学 报 Vol.16, No.6 基于遗传算法重采样的人脸样本扩张 1+ 1，2 1，2 陈杰 , 陈熙霖 , 高文 1(哈尔滨工业大学 计算机学院,黑龙江省哈尔滨市 150001) 2( 中国科学院计算所 ICT-ISVISION 面像识别联合实验室 北京 100080) Expand Training Set for Face Detection by GA Re-sampling CHEN Jie1+, CHEN Xi-Lin 1,2 , GAO Wen1,2 1(School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China) 2(Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080, China) + Corresponding author: Phn: +86-10-5885-8300, Fax: +86-10-5885-8301, E-mail: chenjie@, Received 2004-04-29; Accepted 2004-12-08 CHEN J, CHEN XL, Name GAO W. Expand Training Set for Face Detection by GA Re-sampling. Journal of Software, 2004, 15(1):0000~0000. /1000-9825/16/0000.htm Abstract : Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. All of the statistical methods suffer from this problem. This paper presents a genetic algorithm (GA)-based method to swell face database through re-sampling from existing faces. The basic idea is that a face is composed of a limited components set, and the GA can simulate the procedure of heredity. This simulation can also cover the variations of faces in different lighting conditions, poses, accessories, and quality conditions. To verify the generalization capability of the proposed method, we also use the expanded database to train an AdaBoost-based face detector and test it on the MIT+CMU frontal face test set. The experimental results show that the data collection can be speeded up efficiently by the proposed methods. Key words: face detection; genetic algorithm; SNoW; AdaBoost 摘 要: 无论是对人脸检测还是人脸识别来说，训练或测试一个分类器都要进行数据的收集，目前所有基于统