%0 Journal Article
%T Kernel sparsity preserving projections and its application to gait recognition<br>核稀疏保留投影及在步态识别中的应用
%A Wang Kejun
%A Yan Tao
%A L&#
%A Zhuowen
%A Tang Mo
%A <br>王科俊
%A 阎涛
%A 吕卓纹
%A 唐墨
%J 中国图象图形学报
%D 2013
%I 
%X In order to solve the problem of the curse of dimensionality and the small sample problem, a kernel sparsity preserving projection is proposed. First, the nonlinear transformation is used to map the original data to a high-dimensional feature space. Then, the sparsity reconstruction in a high-dimensional space is used and, the coefficient matrix is reduced and optimized. Finally, the projection matrix is obtained. This method is evaluated on the CASIA (B) Gait database. The experimental results show that the proposed method can obtain stable classification and performs satisfactory recognition results.
%K sparsity preserving projections
%K kernel method
%K gait recognition
%K gait energy image<br>稀疏保留投影
%K 核方法
%K 步态识别
%K 步态能量图
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=2C0F2EE71B46795FA3E0F1FE07E3D3CF&yid=FF7AA908D58E97FA&vid=13553B2D12F347E8&iid=38B194292C032A66&sid=4290346F7268639E&eid=96A53C367B5173D7&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=14