Face Feature Extraction Based on Principle Discriminant Information Analysis

摘要：

A general and efficient face feature extraction approach is presented which utilizes principle discriminant information of human faces. In order to get rid of redundant information and meanwhile reduce computational burden, we first compute the nonzero feature space of training set scatter matrix, and then perform a global search on it to seek out the most valuable discriminant information of faces. Genetic algorithm is used for searching because of its well-known global search ability. This strategy has achieved good performance in terms of recognition rate, computational cost and extended capability on ORL face database. Experiment shows this approach works much better than common used Principle Component Analysis (PCA) method.

关键词： Face feature extraction face recognition principal discriminant information global search genetic algorithm PCA

作者: Jianqin Yin Yuelong Li Jinping Li

作者单位: School of Information Science and Engineering University of Jinan 106 Jiwei Road, Jinan, Shandong, PR China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）