%0 Journal Article
%T Consistence segmentation of triangle mesh using Laplace spectral embedding and Mean Shift<br>基于Laplace谱嵌入和Mean Shift的 三角网格一致性分割
%A Ma Yaqi
%A Li Zhongke
%A Zhao Jing
%A <br>马亚奇
%A 李忠科
%A 赵静
%J 中国图象图形学报
%D 2012
%I 
%X In order to overcome the disadvantage of being sensitive to model gesture and noise in the present mesh segmentation algorithms,we present a consistent mesh segmentation algorithm based on Laplace spectral embedding and Mean Shift. We convert mesh into a normal form from the space domain to the spectral domain by using the Laplace-Beltrami operator. The noise is suppressed and spectral embedding enhances the structural segmentability. We adopt Mean Shift,a nonparametric kernel clustering technique,to gain the visual meaningful semantic patch or sub-mesh in the spectral domain. The experiment results show that the proposed algorithm can yield meaningful result rapidly and effectively for meshes which has an evident branch structure.Meanwhile,this approach is invariant to pose of model and robust to noise.
%K Laplace spectral embedding
%K Mean Shift
%K consistence segmentation
%K triangle mesh<br>Laplace谱嵌入
%K Mean
%K Shift
%K 一致分割
%K 三角网格
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=5B7C7E7B3FC348D3EDF0749099892928&yid=99E9153A83D4CB11&vid=BCA2697F357F2001&iid=F3090AE9B60B7ED1&sid=9438DF4A1CE63979&eid=F8085F090F1A1511&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=16