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Remote Sens. 2016, 8(5), 419; doi:10.3390/rs8050419

Building Point Detection from Vehicle-Borne LiDAR Data Based on Voxel Group and Horizontal Hollow Analysis

1,2
,
1,2,3,4,* , 1,2
,
1,2
and
1,2,3,4,*
1
Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210093, China
2
Department of Geographic Information Science, Nanjing University, Nanjing 210093, China
3
Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University, Nanjing 210093, China
4
Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210093, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Randolph H. Wynne and Prasad S. Thenkabail
Received: 11 March 2016 / Revised: 16 April 2016 / Accepted: 20 April 2016 / Published: 17 May 2016
View Full-Text   |   Download PDF [11803 KB, uploaded 17 May 2016]   |  

Abstract

Information extraction and three-dimensional (3D) reconstruction of buildings using the vehicle-borne laser scanning (VLS) system is significant for many applications. Extracting LiDAR points, from VLS, belonging to various types of building in large-scale complex urban environments still retains some problems. In this paper, a new technical framework for automatic and efficient building point extraction is proposed, including three main steps: (1) voxel group-based shape recognition; (2) category-oriented merging; and (3) building point identification by horizontal hollow ratio analysis. This article proposes a concept of “voxel group” based on the voxelization of VLS points: each voxel group is composed of several voxels that belong to one single real-world object. Then the shapes of point clouds in each voxel group are recognized and this shape information is utilized to merge voxel group. This article puts forward a characteristic nature of vehicle-borne LiDAR building points, called “horizontal hollow ratio”, for efficient extraction. Experiments are analyzed from two aspects: (1) building-based evaluation for overall experimental area; and (2) point-based evaluation for individual building using the completeness and correctness. The experimental results indicate that the proposed framework is effective for the extraction of LiDAR points belonging to various types of buildings in large-scale complex urban environments. View Full-Text
Keywords: vehicle-borne LiDAR; building point extraction; voxel group; horizontal hollow analysis vehicle-borne LiDAR; building point extraction; voxel group; horizontal hollow analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, Y.; Cheng, L.; Chen, Y.; Wu, Y.; Li, M. Building Point Detection from Vehicle-Borne LiDAR Data Based on Voxel Group and Horizontal Hollow Analysis. Remote Sens. 2016, 8, 419.

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