%0 Journal Article
%T 3D Facial Gender Classification Based on Multi-angle LBP Feature<br>基于多角度LBP特征的三维0.3人脸性别分类
%A ZHAO Hai-Ying
%A YANG Yi-Fan
%A XU Zheng-Guang
%A <br>赵海英
%A 杨一帆
%A 徐正光
%J 自动化学报
%D 2012
%I 
%X Facial gender classification is a challenging topic, and it's still not perfect until now. In this paper, we propose a series of methods of gender classification based on three-dimension faces. Automatic front-pose adjustment is needed through local region iterative closest point (ICP) registration firstly; then we do pitching rotating and extract multi-angle LBP features from depth thumbnail map in different viewing angles; at last, we use support vector machine (SVM) classifier to do training and prediction. This algorithm has been experimented on CASIA database, and for the neutral faces in this database, we can get a highest correct classification rate of 98.374%.
%K 3D face
%K gender classification
%K local region iterative closest point (ICP)
%K depth thumbnail map
%K multi-angle LBP<br>三维人脸
%K 性别分类
%K 局部区域最近邻点迭代算法
%K (Iterative
%K closest
%K point
%K ICP)
%K 深度缩略图
%K 多角度LBP
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=21CB0722CA48644F217C4484CBDA5C46&yid=99E9153A83D4CB11&vid=16D8618C6164A3ED&iid=9CF7A0430CBB2DFD&sid=E2EDBBF9B5CDD657&eid=B32C18974698DFB1&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=20