Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments

Bisheng Yang; Zhen Dong; Wenxia Dai; Yuan Liu

doi:10.1109/ICSDM.2015.7298041

Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments

Bisheng Yang, Zhen Dong, Wenxia Dai, Yuan Liu

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

3 Citations (Scopus)

Abstract

This paper proposes a method to automatically register multi-view Terrestrial Laser Scanning Point Clouds in complex urban environment. Firstly, the point cloud segmentation method is applied to cluster the cross-section by self-adaptive distance cluster algorithm. Then, geometric primitives are extracted from point clouds by fitting lines or cylinders, whose spatial continuity is used to extract feature lines and feature triangles. Next, triangles are matched according to their similarity and mismatches are rejected based on geometric constraint. Finally, the proposed method registers multi-view point clouds by constructing a minimum spanning tree of weighted undirected graph. Experimental results show that our method is feasible and it improves the efficiency and precision of registration in urban environment.

Original language	English
Title of host publication	ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services
Editors	Chongcheng Chen, Diansheng Guo, Yee Leung
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	141-146
Number of pages	6
ISBN (Electronic)	9781479977482
DOIs	https://doi.org/10.1109/ICSDM.2015.7298041
Publication status	Published - 13 Oct 2015
Externally published	Yes
Event	2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015 - Fuzhou, China Duration: 8 Jul 2015 → 10 Jul 2015

Publication series

Name	ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services

Conference

Conference	2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015
Country/Territory	China
City	Fuzhou
Period	8/07/15 → 10/07/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

cluster with self-adaptive distance
feature line extraction
geometric constraint
multi-view registration
terrestrial laser scanner point clouds

Access to Document

10.1109/ICSDM.2015.7298041

Cite this

Yang, B., Dong, Z., Dai, W., & Liu, Y. (2015). Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments. In C. Chen, D. Guo, & Y. Leung (Eds.), ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (pp. 141-146). Article 7298041 (ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSDM.2015.7298041

Yang, Bisheng ; Dong, Zhen ; Dai, Wenxia et al. / Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments. ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. editor / Chongcheng Chen ; Diansheng Guo ; Yee Leung. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 141-146 (ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services).

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title = "Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments",

abstract = "This paper proposes a method to automatically register multi-view Terrestrial Laser Scanning Point Clouds in complex urban environment. Firstly, the point cloud segmentation method is applied to cluster the cross-section by self-adaptive distance cluster algorithm. Then, geometric primitives are extracted from point clouds by fitting lines or cylinders, whose spatial continuity is used to extract feature lines and feature triangles. Next, triangles are matched according to their similarity and mismatches are rejected based on geometric constraint. Finally, the proposed method registers multi-view point clouds by constructing a minimum spanning tree of weighted undirected graph. Experimental results show that our method is feasible and it improves the efficiency and precision of registration in urban environment.",

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author = "Bisheng Yang and Zhen Dong and Wenxia Dai and Yuan Liu",

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Yang, B, Dong, Z, Dai, W & Liu, Y 2015, Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments. in C Chen, D Guo & Y Leung (eds), ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services., 7298041, ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Institute of Electrical and Electronics Engineers Inc., pp. 141-146, 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015, Fuzhou, China, 8/07/15. https://doi.org/10.1109/ICSDM.2015.7298041

Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments. / Yang, Bisheng; Dong, Zhen; Dai, Wenxia et al.
ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. ed. / Chongcheng Chen; Diansheng Guo; Yee Leung. Institute of Electrical and Electronics Engineers Inc., 2015. p. 141-146 7298041 (ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments

AU - Yang, Bisheng

AU - Dong, Zhen

AU - Dai, Wenxia

AU - Liu, Yuan

PY - 2015/10/13

Y1 - 2015/10/13

N2 - This paper proposes a method to automatically register multi-view Terrestrial Laser Scanning Point Clouds in complex urban environment. Firstly, the point cloud segmentation method is applied to cluster the cross-section by self-adaptive distance cluster algorithm. Then, geometric primitives are extracted from point clouds by fitting lines or cylinders, whose spatial continuity is used to extract feature lines and feature triangles. Next, triangles are matched according to their similarity and mismatches are rejected based on geometric constraint. Finally, the proposed method registers multi-view point clouds by constructing a minimum spanning tree of weighted undirected graph. Experimental results show that our method is feasible and it improves the efficiency and precision of registration in urban environment.

AB - This paper proposes a method to automatically register multi-view Terrestrial Laser Scanning Point Clouds in complex urban environment. Firstly, the point cloud segmentation method is applied to cluster the cross-section by self-adaptive distance cluster algorithm. Then, geometric primitives are extracted from point clouds by fitting lines or cylinders, whose spatial continuity is used to extract feature lines and feature triangles. Next, triangles are matched according to their similarity and mismatches are rejected based on geometric constraint. Finally, the proposed method registers multi-view point clouds by constructing a minimum spanning tree of weighted undirected graph. Experimental results show that our method is feasible and it improves the efficiency and precision of registration in urban environment.

KW - cluster with self-adaptive distance

KW - feature line extraction

KW - geometric constraint

KW - multi-view registration

KW - terrestrial laser scanner point clouds

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BT - ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services

A2 - Chen, Chongcheng

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PB - Institute of Electrical and Electronics Engineers Inc.

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Yang B, Dong Z, Dai W, Liu Y. Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments. In Chen C, Guo D, Leung Y, editors, ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services. Institute of Electrical and Electronics Engineers Inc. 2015. p. 141-146. 7298041. (ICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services). doi: 10.1109/ICSDM.2015.7298041

Automatic registration of multi-view terrestrial laser scanning point clouds in complex urban environments

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Keywords

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