%0 Journal Article
%T Adaptive Mesh Reconstruction of Point Cloud with Feature Preserved<br>保持特征的点云自适应网格重建
%A QIAN Guiping
%A TONG Ruofeng
%A PENG Wen
%A DONG Jinxiang
%A <br>钱归平
%A 童若锋
%A 彭 文
%A 董金祥
%J 中国图象图形学报
%D 2009
%I 
%X There is noise and defective data on the 3D scanning point cloud. A robust mesh reconstruction algorithm is proposed. Surface normals are estimated by tensor matrix with enhanced features. By computing 3D fast Fourier transform (FFT), discrete iso-surface is extracted. Points are moved onto the iso-surface by an iterative clustering along gradient field, where the noise and outliers are removed and defective data are repaired. Point cloud is decimated adaptively, and then a new triangle is generated using sphere-intersected method. The experimental results have shown that the algorithm is fast, robust and use low memory.
%K reverse engineering
%K Fourier transform
%K meshing
%K denoising<br>逆向工程
%K 傅里叶变换
%K 网格化
%K 降噪
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=79956FB3439B11397FC5F2726EBE4A26&yid=DE12191FBD62783C&vid=F3583C8E78166B9E&iid=CA4FD0336C81A37A&sid=856C2E13D1000DB7&eid=E2546871E5B846EF&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=1&reference_num=13