A global optimization approach to roof segmentation from airborne lidar point clouds |
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| Institution: | 1. School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Rd., 430079 Wuhan, China;2. School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA;3. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Rd., 430079 Wuhan, China;1. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Gaoxin West District, Chengdu, China;2. Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan, China;3. Department of Land Surveying and Geo-Informatics, The Polytechnic University of Hong Kong, Hum Hom, Kowloon, Hong Kong;1. Geomatics Engineering, School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, United States;2. U.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi, MD 20783, United States |
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| Abstract: | This paper presents a global plane fitting approach for roof segmentation from lidar point clouds. Starting with a conventional plane fitting approach (e.g., plane fitting based on region growing), an initial segmentation is first derived from roof lidar points. Such initial segmentation is then optimized by minimizing a global energy function consisting of the distances of lidar points to initial planes (labels), spatial smoothness between data points, and the number of planes. As a global solution, the proposed approach can determine multiple roof planes simultaneously. Two lidar data sets of Indianapolis (USA) and Vaihingen (Germany) are used in the study. Experimental results show that the completeness and correctness are increased from 80.1% to 92.3%, and 93.0% to 100%, respectively; and the detection cross-lap rate and reference cross-lap rate are reduced from 11.9% to 2.2%, and 24.6% to 5.8%, respectively. As a result, the incorrect segmentation that often occurs at plane transitions is satisfactorily resolved; and the topological consistency among segmented planes is correctly retained even for complex roof structures. |
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| Keywords: | Segmentation City modeling Buildings Lidar Point clouds Global optimization |
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