A density-adaptive building boundary extraction method based on 3D point clouds obtained from oblique photogrammetry

doi:10.13474/j.cnki.11-2246.2022.0263

Abstract

Abstract: To tackle the problems of individual building segmentation, this paper proposes an automatic building boundary segmentation method for point clouds derived from the oblique photogrammetry. First, the ground and noise points are filtered out through the pre-processing stage. Then, the point clouds are voxelized for the segmentation. An improved Otsu method and the distance-based region-growing algorithm are integrated to apply to the voxelized point clouds for the boundary extraction. We verify the proposed method with two datasets captured in the Jiangmen and Zhanjiang of the Guangdong Province. The results show that the segmentation accuracy achieve 87.8% and 92.3% for Jiangmen and Zhanjiang datasets, respectively. This suggests that the proposed method is highly applicable to the building segmentation.

Key words: oblique photography, monomerization, feature extraction, cluster segmentation, point clouds

CLC Number:

P237

LIU Yuqi, CHEN Guangliang, CAI Yuezhen, LI Minghao, CHEN Dingan, HU Xiaozhong. A density-adaptive building boundary extraction method based on 3D point clouds obtained from oblique photogrammetry[J]. Bulletin of Surveying and Mapping, 2022, 0(9): 52-57.

References

[1] 孙杰, 谢文寒, 白瑞杰. 无人机倾斜摄影技术研究与应用[J]. 测绘科学, 2019, 44(6):145-150.
[2] 喜文飞, 李国柱, 赵子龙, 等. 倾斜摄影测量技术在不动产测绘中的应用研究[J]. 城市勘测, 2019(1):70-74.
[3] 付博, 陈姗, 张俊. 无人机倾斜摄影测量技术在三维数字城市建模中的应用[J]. 湖南工业大学学报, 2019, 33(5):79-83.
[4] 李云帆, 龚威平, 林俞先, 等. LiDAR点云与影像相结合的建筑物轮廓信息提取[J]. 国土资源遥感, 2014, 26(2):54-59.
[5] 杜守基, 邹峥嵘, 张云生, 等. 融合LiDAR点云与正射影像的建筑物图割优化提取方法[J]. 测绘学报, 2018, 47(4):519-527.
[6] 程效军, 程小龙, 胡敏捷, 等. 融合航空影像和LIDAR点云的建筑物探测及轮廓提取[J]. 中国激光, 2016, 43(5):253-261.
[7] 赵文军, 丁智奇, 王泓森. 倾斜实景模型和LiDAR点云数据相融合的不动产测量新方法[J]. 测绘通报, 2021(2):87-92.
[8] TOMLJENOVIC I, TIEDE D, BLASCHKE T. A building extraction approach for airborne laser scanner data utilizing the object based image analysis paradigm[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 52:137-148.
[9] 何雪, 邹峥嵘, 张云生, 等. 面向对象的倾斜摄影测量点云分类方法[J]. 国土资源遥感, 2018, 30(2):87-92.
[10] 韩姗姗, 黄远程, 白穆. 基于DGCNN语义分割的倾斜摄影测量三维点云建筑物分类[J]. 测绘标准化, 2020, 36(3):21-26.
[11] 李娜, 马一薇, 杨洋, 等. 利用RANSAC算法对建筑物立面进行点云分割[J]. 测绘科学, 2011, 36(5):144-145.
[12] ZHANG Wuming, QI Jianbo, WAN Peng, et al. An easy-to-use airborne LiDAR data filtering method based on cloth simulation[J]. Remote Sensing, 2016, 8(6):501.
[13] LIU Huawen, ZHANG Shichao. Noisy data elimination using mutual k-nearest neighbor for classification mining[J]. Journal of Systems and Software, 2012, 85(5):1067-1074.
[14] 韩延明, 陈成, 张琨, 等. 基于高斯拟合的统计滤波算法及其应用[C]//2016中国汽车工程学会年会论文集. 上海:[出版者不详], 2016:1770-1773.
[15] OTSU N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1):62-66.
[16] SANCHEZ J, DENIS F, COEURJOLLY D, et al. Robust normal vector estimation in 3D point clouds through iterative principal component analysis[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 163:18-35.
[17] 潘章明. 一种基于KD树子样的自动聚类方法[J]. 计算机工程与科学, 2011, 33(1):166-170.
[18] 王磊, 段会川. Otsu方法在多阈值图像分割中的应用[J]. 计算机工程与设计, 2008, 29(11):2844-2845.