计算机应用与软件2013，Vol.30Issue(8)：271-274,4.DOI:10.3969/j.issn.1000-386x.2013.08.073
基于改进AdaBoost的快速人脸检测算法
RAPID FACE DETECTION ALGORITHM BASED ON IMPROVED ADABOOST
摘要
Abstract
When applying in face detection,traditional AdaBoost has the problems of asking many feature numbers and slow speed in detection.In light of this,a rapid face detection algorithm based on improved AdaBoost is proposed.On the one hand,dual-threshold weak classifiers are used to replace the traditional single-threshold weak classifier and this has improved the classification capability on single feature.On the other hand,the information entropy is introduced as the metric means of feature relevance,during the feature selection,in each round of cycle only those features with low feature relevance to the selected features will be chosen,therefore the redundant information between the features is reduced.Experimental results show that compared with traditional AdaBoost face detection algorithm,this one can achieve higher detection correct rate using less features,and the detection speed is magnificently enhanced.关键词
人脸检测/AdaBoost算法/特征选择/特征相关度/信息熵Key words
Face detection / AdaBoost algorithm / Feature selection / Feature relevance / Information entropy分类
信息技术与安全科学引用本文复制引用
房宜汕..基于改进AdaBoost的快速人脸检测算法[J].计算机应用与软件,2013,30(8):271-274,4.基金项目
梅州市科学技术局、嘉应学院联合自然科学研究项目(2010KJA24). （2010KJA24）
