|Table of Contents|

Optimal Registration Method of Surface Point Cloud Model(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2018年01期
Page:
64-
Research Field:
计算机工程
Publishing date:

Info

Title:
Optimal Registration Method of Surface Point Cloud Model
Author(s):
Zhao Fuqun1; 2
(1.School of Education Science,Xianyang Normal University,Xianyang 712000,China)(2.Shool of Information Science and Technology,Northwest University,Xi’an 710127,China)
Keywords:
surface registration; coarse matching; iterative closest point; Gaussian probability; active iterative coefficient
PACS:
TP391
DOI:
10.3969/j.issn.1672-1292.2018.01.009
Abstract:
Aiming at the registration problem of 3D point cloud data models of surfaces with low overlapping,a registration method form coarse to fine is proposed. Firstly,based on Gauss-Helmert least-squares 3D(GH-LS3D),a registration algorithm is used to complete coarse registration. Secondly,an improved iterative closest point(ICP)algorithm which integrated Gaussian probability model and active iterative coefficient to ICP algorithm is proposed to improve the anti-noise capability and convergence rate,and the faster and more accurate registration of surfaces is achieved. The experimental results show that the proposed method can complete accurate surfaces registration,and obtain higher registration accuracy and convergence rate in fine registration stage. Therefore,the optimal registration method is an effective surface registration method.

References:

[1] LIN S Z,WANG D J,ZHONG J R. Approach to reassembling virtual small bronze fragments using the curvature feature[J]. Journal of Xidian university,2016(46):12,151-156.
[2]ROTH J,TONG Y,LIU X. Adaptive 3D face reconstruction from unconstrained photo collections[J]. IEEE transactions on pattern analysis and machine intelligence,2017(99):2 127-2 141.
[3]汪前进,朱斌,李存华. 基于特征点的图像拼接方法的研究与应用[J]. 南京师范大学学报(工程技术版),2016,16(3):48-53.
WANG Q J,ZHU B,LI C H. Research and application of image stitching method based on feature points[J]. Journal of Nanjing normal university(engineering and technology edition),2016,16(3):48-53.(in Chinese)
[4]张天安,云挺,薛联凤,等. 基于骨架提取的树木主枝干三维重建算法[J]. 南京师范大学学报(工程技术版),2014,14(4):51-57.
ZHANG T A,YUN T,XUE L F,et al. Three-dimensional reconstruction algorithm of tree limbs based on skeleton extraction[J]. Journal of Nanjing normal university(engineering and technology edition),2014,14(4):51-57.(in Chinese)
[5]CROOK S,MEGHAN C,MAARTEN B,et al. Can a semi-automated surface matching and principal axis-based algorithm accurately quantify femoral shaft fracture alignment in six degrees of freedom[J]. Medical engineering and physics,2013,35(7):1 028-1 036.
[6]BABA T,MATSUOKA R,SHIRAI K,et al. Misaligned image integration with local linear model[J]. IEEE transactions on image processing,2016,25(5):2 035-2 044.
[7]BESL P J,MCKAY N D. A method for registration of 3-D shapes[J]. IEEE transactions on pattern analysis and machine intelligence,1992,14(2):239-256.
[8]王欣,张明明,于晓,等. 应用改进迭代最近点方法的点云数据配准[J]. 光学精密工程,2012,20(9):2 068-2 077.WANG X,ZHANG M M,YU X,et al. Point cloud registration based on improved iterative closest point method[J]. Optics and precision engineering,2012,20(9):2 068-2 077.(in Chinese)
[9]LI W,SONG P. A modified ICP algorithm based on dynamic adjustment factor for registration of point cloud and CAD model[J]. Pattern recognition letters,2015,65:88-94.
[10]MAVRIDIS P,AABDREDIS A,PAPAIOANNOU G. Efficient sparse ICP[J]. Computer aided geometric design,2015,35(C):16-26.
[11]DU S,LIU J,ZHANG C. Probability iterative closest point algorithm for m-D point set registration with noise[J]. Neurocomputing,2015,157(CAC):187-198.
[12]DU S,ZHENG N,XIONG L. Scaling iterative closest point algorithm for registration of m-D point sets[J]. Journal of visual communication and image representation,2010,21(5-6):442-452.
[13]GRUEN A,ACKA D. Least squares 3D surface and curve matching[J]. ISPRS J Photogramm Remote Sens,2005,59:151-174.
[14]Stanford University. The Stanford 3D Scanning Repository[EB/OL]. [2017-03-10]http://graphics.stanford.edu/data/3Dscanrep.

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