%0 Journal Article
%T Abnormal Human Behaviors Recognition Based on W2KPCA-KNN Algorithm<br>基于W2KPCA-KNN算法的人体异常行为识别
%A LOU Zhong-Wang
%A YAO Ming-Hai
%A Qu Xin-Yu
%A RUAN Tao-Tao
%A ZHU Xiao-Ming
%A <br>楼中望
%A 姚明海
%A 瞿心昱
%A 阮涛涛
%A 朱晓明
%J 计算机系统应用
%D 2011
%I 
%X The recognition based on vision to extract features from abnormal human behaviors usually utilize straightforward sharp movement information or traditional PCA methods. The former lacks of information and the latter has ignored nonlinear information in data. Therefore, this paper will use KPCA in recognizing abnormal human behaviors to solve the aforementioned problems. Since KPCA has some defects in extracting feature abnormal behaviors, W2KPCA-KNN algorithm is proposed, which is to do weighting in both feature extraction and classification respectively. While retaining behavioral information in the image, it improves recognition accuracy and satisfies the technical requirements for abnormal behavior recognition system. The experimental comparisons show that this algorithm outperforms traditional KPCA and K-Nearest Neighbor classifier on both feature extraction and classification.
%K KPCA
%K KNN
%K abnormal human behaviors
%K weight<br>PCA
%K KPCA
%K KNN
%K 人体异常行为
%K 加权运算
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=2EE33D37689C9E6EE06B2EB6183150AE&yid=9377ED8094509821&vid=A04140E723CB732E&iid=0B39A22176CE99FB&sid=0B4F496D54044D86&eid=1B97AE5098AEB49C&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=13