35th International Symposium on Remote Sensing of Environment | |
A comprehensive framework of building model reconstruction from airborne LiDAR data | |
地球科学;生态环境科学 | |
Xiao, Y.^1,2 ; Wang, C.^1 ; Xi, X.H.^1 ; Zhang, W.M.^3 | |
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, China^1 | |
University of Chinese Academy of Sciences, Beijing, China^2 | |
Beijing Normal University, Beijing, China^3 | |
关键词: 3D building models; Airborne lidar data; Building extraction; Building model reconstruction; Connected component analysis; Lidar point clouds; Region growing algorithm; Segmentation results; | |
Others : https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012178/pdf DOI : 10.1088/1755-1315/17/1/012178 |
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学科分类:环境科学(综合) | |
来源: IOP | |
【 摘 要 】
This paper presents a comprehensive framework of reconstructing 3D building models from airborne LiDAR data, which involves building extraction, roof segmentation and model generation. Firstly, building points are extracted from LiDAR point clouds by removing walls, trees, ground and noises. Walls and trees are identified by the normal and multi-return features respectively and then ground and noise are detected by the region growing algorithm which aims at extracting smooth surfaces. Then the connected component analysis is performed to extract building points. Secondly, once the building points are acquired, building roofs are separated by the region growing algorithm which employs the normal vector and curvature of points to detect planar clusters. Finally, by combining regular building outlines obtained from building points and roof intersections acquired from the roof segmentation results, 3D building models with high accuracy are derived. Experimental results demonstrate that the proposed method is able to correctly obtain building points and reconstruct 3D building models with high accuracy.
【 预 览 】
Files | Size | Format | View |
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A comprehensive framework of building model reconstruction from airborne LiDAR data | 445KB | download |