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Proceedings Paper

A novel building boundary reconstruction method based on lidar data and images
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Paper Abstract

Building boundary is important for the urban mapping and real estate industry applications. The reconstruction of building boundary is also a significant but difficult step in generating city building models. As Light detection and ranging system (Lidar) can acquire large and dense point cloud data fast and easily, it has great advantages for building reconstruction. In this paper, we combine Lidar data and images to develop a novel building boundary reconstruction method. We use only one scan of Lidar data and one image to do the reconstruction. The process consists of a sequence of three steps: project boundary Lidar points to image; extract accurate boundary from image; and reconstruct boundary in Lidar points. We define a relationship between 3D points and the pixel coordinates. Then we extract the boundary in the image and use the relationship to get boundary in the point cloud. The method presented here reduces the difficulty of data acquisition effectively. The theory is not complex so it has low computational complexity. It can also be widely used in the data acquired by other 3D scanning devices to improve the accuracy. Results of the experiment demonstrate that this method has a clear advantage and high efficiency over others, particularly in the data with large point spacing.

Paper Details

Date Published: 19 September 2013
PDF: 7 pages
Proc. SPIE 8905, International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications, 890522 (19 September 2013); doi: 10.1117/12.2034748
Show Author Affiliations
Yiming Chen, Beijing Normal Univ. (China)
State Key Lab. of Remote Sensing Science (China)
Beijing Key Lab. of Environmental Remote Sensing and Digital City (China)
Wuming Zhang, Beijing Normal Univ. (China)
State Key Lab. of Remote Sensing Science (China)
Beijing Key Lab. of Environmental Remote Sensing and Digital City (China)
Guoqing Zhou, Guilin Univ. of Technology (China)
Guangjian Yan, Beijing Normal Univ. (China)
State Key Lab. of Remote Sensing Science (China)
Beijing Key Lab. of Environmental Remote Sensing and Digital City (China)


Published in SPIE Proceedings Vol. 8905:
International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications
Farzin Amzajerdian; Astrid Aksnes; Weibiao Chen; Chunqing Gao; Yongchao Zheng; Cheng Wang, Editor(s)

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