Optimal Extraction of Building Key Planes Based on Statistical Values of Community Building Characteristics

Yin Liu; Fangqiang Yu; Peng Wang; Peikang Xin

doi:10.16670/j.cnki.cn11-5823/tu.2024.03.12

Citation: Yin Liu, Fangqiang Yu, Peng Wang, Peikang Xin. Optimal Extraction of Building Key Planes Based on Statistical Values of Community Building Characteristics. Journal of Information Technologyin Civil Engineering and Architecture, 2024, 16(3): 65-70. doi: 10.16670/j.cnki.cn11-5823/tu.2024.03.12

2024, 16(3): 65-70. doi: 10.16670/j.cnki.cn11-5823/tu.2024.03.12

Optimal Extraction of Building Key Planes Based on Statistical Values of Community Building Characteristics

Yin Liu , Fangqiang Yu , Peng Wang , Peikang Xin ^,

Shanghai Construction No. 4(Group)Co., Ltd., Shanghai 201103, China

Corresponding author: 辛佩康,

Web Publishing Date: 2024-06-20

Fund Project: 上海市国资委企业创新发展和能级提升项目 2022008

Over-segmentation caused by conventional RANSAC plane segmentation and extraction frequently occurs in oblique photographic point cloud plane segmentation of complex building shapes. In this paper, combined with the characteristics of building point clouds in oblique photography, a single building key plane segmentation and extraction method based on the statistical values of architectural features within the community is proposed. Firstly, the planes were merged according to the statistical values of the distance and angle of the building planes in the community. Secondly, the vertical plane was optimized according to the slope statistics. Thirdly, the plane was filtered and optimized according to the statistical value of plane point density and the characteristic structure. Finally, the optimal extraction of key building planes was realized. It has been verified that this method has an accuracy rate of 95.80% and a recall rate of 96.21% for the extraction of key feature plane information e.g. the bottom plane, wall, and roof of a single building, which can provide the basic data for the subsequent automatic construction of building information modeling.

Key words: Community Building, Oblique Photography Point Cloud, Feature Statistics, Plane Extraction, Building Individualization

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Optimal Extraction of Building Key Planes Based on Statistical Values of Community Building Characteristics

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