Research Papers

Automatic registration of laser point cloud using precisely located sphere targets

[+] Author Affiliations
Yanmin Wang

Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, 129 Luoyu Road, Wuhan, 430079, China

Beijing University of Civil Engineering and Architecture, Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, 1 Zhanlanguan Road, Beijing, 100044, China

Hongbin Shi

Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, 129 Luoyu Road, Wuhan, 430079, China

Yanyan Zhang

Beijing University of Civil Engineering and Architecture, Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, 1 Zhanlanguan Road, Beijing, 100044, China

Dongmei Zhang

Beijing University of Civil Engineering and Architecture, Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, 1 Zhanlanguan Road, Beijing, 100044, China

J. Appl. Remote Sens. 8(1), 083588 (Jul 18, 2014). doi:10.1117/1.JRS.8.083588
History: Received December 13, 2013; Revised May 29, 2014; Accepted June 17, 2014
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Abstract.  Sphere targets are used extensively in terrestrial laser scanning registration; however, in practice, it is still a time-consuming and labor-intensive task. This paper proposes an automatic registration method for laser point clouds based on sphere targets’ detection. First, a modified eight-neighbors check method is applied to mark occluding edge points. Then, for the sphere targets in the raster structure, occluding edge points are clustered, and circle and sphere detections are sequentially implemented in the cluster node and circular area, respectively. The sphere models that pass through multilevel constraints are considered the final results. Next, triangles constructed using three arbitrary noncollinear sphere centers in each scan station are selected as registration primitives and the area and interior angles of each are selected as similarity measures. Finally, the congruent sphere centers between two scan stations are matched in an iterative manner and used to calculate the transformation matrix. The results of experiments in which a lab was scanned from two locations indicate that our method can effectively detect four sphere targets in more than 10 million point clouds within 1.5min, with the largest position error between congruent points <2mm.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Yanmin Wang ; Hongbin Shi ; Yanyan Zhang and Dongmei Zhang
"Automatic registration of laser point cloud using precisely located sphere targets", J. Appl. Remote Sens. 8(1), 083588 (Jul 18, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083588


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