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An improved RANSAC algorithm for building point clouds segmentation in consideration of roof structure |
| LI Yunfan1, TAN Debao1, LIU Rui2,3, WU Jianwei4,5 |
1. Yangtze River Scientific Research Institute, Wuhan 430010, China;
2. Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055,China;
3. Center for Assessment and Development of Real Estate, Shenzhen 518040, China;
4. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100830, China;
5. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430029, China |
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Abstract An improved RANSAC algorithm was proposed for point cloud segmentation and geometric primitives extraction of buildings with multiple facets and complex roof structures, including two innovations. Firstly, the “split-segment” strategy combined with regional growth concept is proposed to improve the segment result and efficiency of classic RANSAC algorithm; Secondly, an improved RANSAC algorithm with variant consensus set threshold is presented. By automatically adjusting the consensus set threshold value, geometric primitives with scale difference are likely to meet the validity test, thus avoiding the over-segmentation and under- segmentation problems of classic RANSAC algorithm with fixed consensus set threshold.
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| Keywords
GIOVANNI
AOD
atmospheric particles
remote sensing
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Issue Date: 04 December 2017
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2017,
Vol. 29
