%0 Journal Article
%T Improvement of Adaboost face detection<br>Adaboost人脸检测方法的改进
%A WEI Dong-sheng
%A LI Lin-qing
%A <br>魏冬生
%A 李林青
%J 计算机应用
%D 2006
%I 
%X Aiming at the problem that training time of Adaboost face detection is extremely long, two improvement methods were proposed:One method was to directly solve the parameter of single weaker classifier,the other was to introduce a double threshold decision to make stronger classifier.The experiment results show that the number of weaker classifiers needed in Adaboost face detection system updated is dramatically reduced and its training speed is about 11 times higher than that of the traditional method.
%K face detection
%K pattern recognition
%K threshold
%K Adaboost algorithm<br>人脸检测
%K 模式识别
%K 阈值
%K Adaboost算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=912CBA77B3AEFD39&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=38B194292C032A66&sid=06D504E5261AB652&eid=F9ADE9F93162E1B0&journal_id=1001-9081&journal_name=计算机应用&referenced_num=7&reference_num=6