Valley-ridge feature extraction from point clouds

ZHANG Yu-he; GENG Guo-hua; WEI Xiao-ran

doi:10.3788/OPE.20152301.0310

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Valley-ridge feature extraction from point clouds

更新时间：2020-08-13

- Valley-ridge feature extraction from point clouds
- Optics and Precision Engineering Vol. 23, Issue 1, Pages: 310-318(2015)
- 作者机构：
  
  西北大学信息科学与技术学院,陕西西安,710127
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152301.0310
  CLC： TP391.4
- Received：03 September 2014，
  
  Revised：01 November 2014，
  
  Published：25 January 2015
- 稿件说明：
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张雨禾, 耿国华, 魏潇然. 散乱点云谷脊特征提取[J]. 光学精密工程, 2015,23(1): 310-318

ZHANG Yu-he, GENG Guo-hua, WEI Xiao-ran. Valley-ridge feature extraction from point clouds[J]. Editorial Office of Optics and Precision Engineering, 2015,23(1): 310-318
张雨禾, 耿国华, 魏潇然. 散乱点云谷脊特征提取[J]. 光学精密工程, 2015,23(1): 310-318 DOI： 10.3788/OPE.20152301.0310.

ZHANG Yu-he, GENG Guo-hua, WEI Xiao-ran. Valley-ridge feature extraction from point clouds[J]. Editorial Office of Optics and Precision Engineering, 2015,23(1): 310-318 DOI： 10.3788/OPE.20152301.0310.

摘要

利用微分"化曲为直"的本质特性和离散计算方法

提出了一种基于局部重建的散乱点云谷脊特征提取算法.首先

利用离散Laplacian算子对点进行增强

通过阈值过滤标记潜在谷脊点.然后

在每个潜在谷脊点的局部邻域内构建紧附于潜在曲面、能反映该点局部几何特征信息的三角网格.最后

根据Weingarten映射的性质

估算潜在谷脊点的主曲率和主方向;将邻域大小作为尺度参数

利用简单直观的离散计算方法及线性插值方法

多尺度地判定一点是否为主方向上的曲率极值点

从而提取谷脊特征.实验结果表明:当点云规模为10 375个

谷脊点规模为1 129个时

执行时间仅为97.39 ms;当点云规模达327 853个

谷脊点规模达到105 482个时

执行时间为3 956.12 ms.该方法简单、稳定

避免了传统的利用拟合曲面再逼近微分量方法中由于曲面拟合带来的高时间代价

能快速有效地提取散乱点的云谷脊特征.

Abstract

On the basis of characteristic of differential "curl to straight" and disperse calculation method

an extraction method using local reconstruction and differential calculation was proposed for valley-ridge features from point clouds. First

the dispersed Laplacian operator was used to enhance the point data and an appropriate threshold was set to obtain potential valley-ridge points. Then

a triangle mesh attached on the potential surface was constructed in every valley-ridge points to effectively reflect the local geometry feature information. Finally

according to Weingarten mapping

principal curvatures and principal directions of potential valley-ridge points were calculated. A simple differential calculation method and a linear interpolation method were used to decide if the point is an extreme value point in principle direction and to extract the valley-ridge features based on the multi-scaling idea. The experimental results indicate that when the number of vertexes and the number of valley-ridge features are 10 375 and 1 129

respectively

the execute time is just 97.39 ms. And when those are 327 853 and 105 482

the execute time is 3 956.12 ms. The method proposed in this paper is simply

stable

and avoids higher time cost due to fitting surface to approximate the differential quantities in the traditional method

so it extracts valley-ridge features from point clouds fast and efficiently.

关键词

Keywords

references

冯筠,陈雨,仝鑫龙,等. 三维颅骨特征点的自动标定 [J]. 光学精密工程,2014,22(5):1388-1394. FENG J,CHEN Y,TONG X L, et al.. Automatic feature point extraction for three-dimensional skull [J].Opt. Precision Eng., 2014,22(5):1388-1394.

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):2068-2077. WANG X,ZHANG M M,YU X, et al..Point cloud registration based on improved interative closest point method [J]. Opt. Precision Eng., 2012,20(9):2068-2077.(in Chinese)

胡事民,杨永亮,来煜坤. 数字几何处理研究进展 [J]. 计算机学报,2009,32(8): 1451-1469. HU SH M, YANG Y L, LAI Y K. Research progress of digital geometry processing [J]. Chinese Journal Computer, 2009, 32(8): 1451-1469. (in Chinese).

FLEISHMAN S, COHEN-OR D, SILVA C T. Robust moving least-squares fitting with sharp features [C]. ACM Transactions on Graphics (TOG),ACM, 2005, 544-552.

KUO C C, YAU H T. A new combinatorial approach to surface reconstruction with sharp features [J]. IEEE Transactions on Visualization and Computer Graphics, 2006, 12(1): 73-82.

GUMHOLD S, WANG X L, MACLEOD. Feature extraction from point clouds [C]. Proceedings of the 10th International Meshing Roundtable, 2001: 293-305.

PAULY M, KEISER R, GROSS M. Multi-scale feature extraction on point-sampled surfaces [J]. Computer Graphics Forum, 2003, 22(3): 281-289.

HO H T, GIBBINS D. Curvature-based approach for multi-scale feature extraction from 3D meshes and unstructured point clouds [J]. IET Computer Vision, 2009, 3(4): 201-212.

DANIELS J, HA L K, OCHOTTA T, et al.. Robust smooth feature extraction from point clouds [C]. Proceedings of the IEEE International Conference on Modeling and Applications, 2007: 123-136.

DEMARSIN K, VANDERSTRAETEN D, VOLODINE T, et al.. Detection of closed sharp edges in point clouds using normal estimation and graph theory [J]. Computer-Aided Design, 2007, 39(4): 276-283.

WEBER C, HAHMANN S, HAGEN H. Sharp feature detection in point clouds [C]. Proceedings of Shape Modeling International Conference, 2010: 175-186.

王小超,刘秀平,李宝军,等. 基于局部重建的点云特征点提取 [J]. 计算机辅助设计与图形学学报, 2013,25(5):659-665. WANG X CH, LIU X P, LI B J, et al.. Feature detection on point cloud via local reconstruction [J]. Journal of Computer-Aided Design & Computer Graphics, 2013, 25(5):659-665.(in Chinese)

庞旭芳,庞明勇,肖春霞. 点云模型谷脊特征的提取与增强算法 [J]. 自动化学报,2010,36(8):1073-1083. PANG X F, PANG M Y, XIAO CH X. An algorithm for extracting and enhancing valley-ridge features from point sets [J]. Acta Automatica Sinica,2010, 32 (8):1073-1083.(in Chinese)

MERIGOT Q, QVAJANIKOV M, GUIBAS L. Voronoi-based curvature and feature estimation from point clouds [J].Visualization and Computer Graphics, 2011, 17(6): 743-756.

吾守尔·斯拉木,曹巨明. 一种新的散乱点云尖锐特征提取方法 [J]. 西安交通大学学报,2012,46(12):1-5,73. WU SHOU ER, CAO J M. An extraction algorithm for sharp feature points from point clouds [J]. Journal of Xi'an Jiaotong University, 2012,46(12):1-5,73.(in Chinese)

李宝,程志全,党岗,等. 三维点云法向量估计综述 [J]. 计算机工程与应用,2010,46(23):1-7. LI B,CHENG ZH Q,DANG G, et al.. Survey on normal estimation for 3D point clouds [J]. Computer Engineering and Applications, 2010,46(23):1-7.(in Chinese)

廖家志. 基于曲面约束的空间Delaunay三角剖分方法研究 [D]. 成都:电子科技大学,2013. LIAO J Z.The research of space Delaunay triangulation constrained by surface [D].Chengdu: University of Electronic Science and Technology of China,2013.(in Chinese)

JUDD T, DURAND F, ADELSON E. Apparent ridges for line drawing [C]. ACM Transactions on Graphics (TOG). ACM, 2007, 26(3): 19.

谭一鸣. 网格模型上脊线与谷线的提取 [D]. 浙江:浙江大学,2010. TAN Y M. Ridges and valleys extraction on meshes [D]. Zhejiang: Zhejiang University, 2010. (in Chinese)

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