%0 Journal Article
%T Demographical Classification by Shape Free Texture and Boosting Learning<br>基于形状无关纹理和Boosting学习的人口统计学分类
%A Yang Zhi-guang Ai Hai-zhou
%A <br>杨之光
%A 艾海舟
%J 电子与信息学报
%D 2008
%I 
%X In this paper, a gender and age classification method, in which age is classified into four classes: child, youth, midlife and agedness, based on shape free texture and boosting learning is introduced. After a face is detected, face alignment extracts 88 facial landmarks by which the face image is normalized to a shape free texture. Further more, three kinds of local feature, Haar like feature, LBP histogram and Gabor jet are extracted from the shape free texture; and boosting learning method is used for training classifiers. The experimental results show that, LBP histogram can be used for robust recognition of children and old people, Haar like feature is more efficient for discriminating young and middle aged people, and Gabor Jet fits for gender classification best.
%K Demographical classification
%K Face image processing
%K Boosting<br>人口统计学分类
%K 人脸图像处理
%K Boosting
%K 基于形状
%K 纹理
%K Boosting
%K 学习
%K 人口
%K 统计学分类
%K Learning
%K Texture
%K Free
%K Shape
%K 性别分类
%K 中年人
%K 儿童
%K 地区
%K 鲁棒
%K 实验
%K 分类器
%K 训练
%K Gabor
%K 直方图
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=AB7DCA316F8D79D0E1D443634B462DF6&yid=67289AFF6305E306&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=569BDAA4FEA0F7F9&eid=94655B9881133A28&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=1&reference_num=16