%0 Journal Article
%T Study of point cloud data reduction algorithm integrating space partition and curvature<br>空间分割与曲率相融合的点云精简算法研究
%A GE Yuan-kun
%A LI Rong
%A LI Hai-lun
%A <br>葛源坤
%A 黎荣
%A 李海伦
%J 计算机应用研究
%D 2012
%I 
%X There are huge amounts of redundant data in point cloud data obtained by non-contact scanning. In order to realize model reconstruction effectively, point cloud data reduction is an indispensable means of pre-processing means. This paper presented an approach of point cloud data reduction based on space partition and curvature. Through some key technologies, such as K-neighborhood search, second surface fitting, curvature estimation, and data partition by of controllable curvature threshold, it applied the different reduction algorithms in different regions of the same point cloud data, meanwhile, achieved realizable reduction proportions. So, the algorithm can ensure reduction efficiency and retain characteristic information of the point cloud data simultaneously.
%K K-neighbors
%K curvature
%K space partition
%K minimum distance
%K bounding box<br>K邻域
%K 曲率
%K 空间分割
%K 最小距离
%K 包围盒
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F886A295C1E57CC5E11B6064A33A1902&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=5370399DC954B911&eid=9806D0D4EAA9BED3&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9