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Remote Sens. 2014, 6(9), 8405-8423; doi:10.3390/rs6098405

Automatic Vehicle Extraction from Airborne LiDAR Data Using an Object-Based Point Cloud Analysis Method

1
School of Resource and Environmental Sciences, Wuhan University, No.129 Luoyu Road, Wuhan 430079, China
2
Chinese Academy of Surveying and Mapping, No. 28 Lianhuachixi Road, Beijing 100830, China
3
National Administration of Surveying, Mapping and Geoinformation, No. 28 Lianhuachixi Road, Beijing 100830, China
*
Authors to whom correspondence should be addressed.
Received: 11 June 2014 / Revised: 7 August 2014 / Accepted: 2 September 2014 / Published: 5 September 2014
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Abstract

Automatic vehicle extraction from an airborne laser scanning (ALS) point cloud is very useful for many applications, such as digital elevation model generation and 3D building reconstruction. In this article, an object-based point cloud analysis (OBPCA) method is proposed for vehicle extraction from an ALS point cloud. First, a segmentation-based progressive TIN (triangular irregular network) densification is employed to detect the ground points, and the potential vehicle points are detected based on the normalized heights of the non-ground points. Second, 3D connected component analysis is performed to group the potential vehicle points into segments. At last, vehicle segments are detected based on three features, including area, rectangularity and elongatedness. Experiments suggest that the proposed method is capable of achieving higher accuracy than the exiting mean-shift-based method for vehicle extraction from an ALS point cloud. Moreover, the larger the point density is, the higher the achieved accuracy is. View Full-Text
Keywords: filtering; digital elevation models; point cloud segmentation; shape; connected component analysis; mean shift filtering; digital elevation models; point cloud segmentation; shape; connected component analysis; mean shift
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Zhang, J.; Duan, M.; Yan, Q.; Lin, X. Automatic Vehicle Extraction from Airborne LiDAR Data Using an Object-Based Point Cloud Analysis Method. Remote Sens. 2014, 6, 8405-8423.

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