Delaunay-based Non-uniform sampling for noisy point cloud

doi:10.11772/j.issn.1001-9081.2014.10.2922

Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (10): 2922-2924.DOI: 10.11772/j.issn.1001-9081.2014.10.2922

Previous Articles Next Articles

Delaunay-based Non-uniform sampling for noisy point cloud

LI Guojun,LI Zongchun,HOU Dongxing

Insitute of Geography Space Information, Information Engineering University, Zhengzhou Henan 450052, China

Received:2014-04-28 Revised:2014-06-20 Online:2014-10-01 Published:2014-10-30
Contact: LI Guojun

基于Delaunay三角化的噪声点云非均匀采样

李国俊,李宗春,侯东兴

信息工程大学地理空间信息学院，郑州 450052

通讯作者: 李国俊
作者简介:李国俊(1990-)，男，湖北武穴人，硕士研究生，主要研究方向：地面三维激光扫描仪、精密工程测量；
李宗春(1973-)，男，山东日照人，教授，博士，主要研究方向：天线测量、工业测量系统、精密工程测量；
侯东兴(1988-)，男，河北保定人，硕士研究生，主要研究方向：地面三维激光扫描仪、精密工程测量。

Abstract

Abstract:

To satisfy ε-sample condition for Delaunay-based triangulation surface reconstruction algorithm, a Delaunay-based non-uniform sampling algorithm for noisy point clouds was proposed. Firstly, the surface Medial Axis (MA) was approximated by the negative poles computed by k-nearest neighbors Voronoi vertices. Secondly, the Local Feature Size (LFS) of surface was estimated with the approximated medial axis. Finally, combined with the Bound Cocone algorithm, the unwanted interior points were removed. Experiments show that the new algorithm can simplify noisy point clouds accurately and robustly while keeping the boundary features well. The simplified point clouds are suitable for Delaunay-based triangulation surface reconstruction algorithm.

摘要：

针对基于Delaunay三角化曲面重建方法要求点云密度满足ε-sample条件，提出了一种基于Delaunay三角化的噪声点云非均匀采样算法。首先,利用k-邻近点的Voronoi顶点计算出各点的负极点来逼近曲面中轴(MA)；然后,根据近似中轴估计出曲面局部特征尺度(LFS)；最后,结合Bound Cocone算法，删除多余的非边界点。实例表明，该算法可以准确、稳健地简化噪声点云，同时可以很好地保留曲面边界特征，经简化后的点云适用于基于Delaunay三角化的曲面重建方法。

CLC Number:

TP391

LI Guojun LI Zongchun HOU Dongxing. Delaunay-based Non-uniform sampling for noisy point cloud[J]. Journal of Computer Applications, 2014, 34(10): 2922-2924.

李国俊李宗春侯东兴. 基于Delaunay三角化的噪声点云非均匀采样[J]. 计算机应用, 2014, 34(10): 2922-2924.

References

［1］ZHU D. PCL manual ［M］. Beijing: Beihang University Press, 2012：359-360.(朱德海. 点云库PCL学习教程［M］. 北京: 北京航空航天大学出版社, 2012：359-360.)
［2］AMENTA N, BERN M. Surface reconstruction by Voronoi filtering ［J］. Discrete and Computational Geometry, 1999,22(4):481-504.
［3］AMENTA N, CHOI S, KOLLURI R K. The power crust ［C］// Proceedings of the 6th ACM Symposium on Solid Modeling and Applications. New York: ACM, 2001:249-266.
［4］AMENTA N, CHOI S, DEY T K, et al.A simple algorithm for homeomorphic surface reconstruction ［C］// Proceedings of the 16th Annual Symposium on Computational Geometry. New York: ACM, 2000:213-222.
［5］DEY T K, GIESEN J. Detecting undersampling in surface recon-struction ［C］// Proceedings of the 17th Annual Symposium on Computational Geometry. New York: ACM, 2001:257-263.
［6］DEY T K, GOSWAMI S. Tight cocone: a water-tight surface reconstructor ［C］// Proceedings of the 8th ACM Symposium on Solid Modeling and Applications. New York: ACM, 2003:127-134.
［7］DEY T K, GOSWAMI S. Provable surface reconstruction from noisy samples ［C］// Proceedings of the 20th Annual Symposium on Computational Geometry. New York: ACM, 2004:330-339.
［8］DEY T K, WANG L. SMI 2013: Voronoi-based feature curves extraction for sampled singular surfaces ［J］. Computers and Graphics, 2013,37(6):659-668.
［9］GAO S, LU H, ZHOU W. A fast algorithm for surface reconstruction from unorganized points ［J］. Journal of Image and Graphics, 2002,7(12):108-112.(高山,卢汉清,周万宁.散乱点的快速曲面重建方法［J］.中国图象图形学报,2002,7(12):108-112.)
［10］NI T, YANG C. A fast surface reconstruction algorithm based on border-estimation for 3D unorganized points ［J］. Journal of Computer Applications, 2006,26(7): 1580-1582.
(倪彤光,杨长春.基于边界检测的三维散乱点快速曲面重建算法［J］.计算机应用,2006,26(7):1580-1582.)
［11］DEY T K. Curve and surface reconstruction: algorithms with mathematical analysis ［M］. Cambridge: Cambridge University Press, 2007:14-16.
［12］AMENTA N, BERN M, KAMVYSSELIS M. A new Voronoi-based surface reconstruction algorithm ［C］// Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM, 1998:415-421.
［13］DEY T K, SUN J. Normal and feature approximations from noisy point clouds ［C］// Proceedings of the 26th International Conference on Foundations of Software Technology and Theoretical Computer Science. Berlin: Springer-Verlag, 2006:21-32.
［14］CGAL. Computational geometry algorithm library ［EB/OL］. ［2014-06-20］. http://www.cgal.org.
［15］VTK. Visualization toolkit ［EB/OL］. ［2014-06-20］. http://www.vtk.org.

[1]	. Statistically significant sequential patterns mining algorithm under influence [J]. Journal of Computer Applications, 0, (): 0-0.
[2]	. Indoor fall detection algorithm based on Res2Net-YOLACT and feature fusion [J]. Journal of Computer Applications, 0, (): 0-0.
[3]	. One-shot video-based person re-identification with multi-loss learning and joint metric [J]. Journal of Computer Applications, 0, (): 0-0.
[4]	. Network embedding method based on multi-granularity community information [J]. Journal of Computer Applications, 0, (): 0-0.
[5]	. Data stream preference query based on extracted sequence according to temporal condition [J]. Journal of Computer Applications, 0, (): 0-0.
[6]	. Multiscale residual UNet based on attention mechanism to realize breast cancer lesion segmentation [J]. Journal of Computer Applications, 0, (): 0-0.
[7]	. Gene data generation method based on generative adversarial network [J]. Journal of Computer Applications, 0, (): 0-0.
[8]	. Prediction of NOx emission from fluid catalytic cracking unit based on ensemble empirical mode decomposition and long short-term memory network [J]. Journal of Computer Applications, 0, (): 0-0.
[9]	. Fundus vessel segmentation method combined with U-Net and adaptive threshold pulse coupled neural network [J]. Journal of Computer Applications, 0, (): 0-0.
[10]	. EE-GAN：Facial expression recognition method based on generative adversarial network and network integration [J]. Journal of Computer Applications, 0, (): 0-0.
[11]	. Recognition algorithm of vehicle logo on traffic road [J]. Journal of Computer Applications, 0, (): 0-0.
[12]	. Multi-modal deep fusion for false information detection [J]. Journal of Computer Applications, 0, (): 0-0.
[13]	. Point cloud registration algorithm based on residual attention mechanism [J]. Journal of Computer Applications, 0, (): 0-0.
[14]	. Low contrast pulp filament defect detection method of non-woven fabric based on deep feature fusion [J]. Journal of Computer Applications, 0, (): 0-0.
[15]	. Pooling algorithm based on Gaussian function [J]. Journal of Computer Applications, 0, (): 0-0.

Delaunay-based Non-uniform sampling for noisy point cloud

基于Delaunay三角化的噪声点云非均匀采样

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics