布料模拟法无人机倾斜摄影建筑点云提取

doi:10.13474/j.cnki.11-2246.2020.0327

测绘通报 ›› 2020, Vol. 0 ›› Issue (10): 97-100.doi: 10.13474/j.cnki.11-2246.2020.0327

布料模拟法无人机倾斜摄影建筑点云提取

王果¹, 王强², 刘绍堂¹, 杨福芹¹, 赵光兴¹, 杨彬³

1. 河南工程学院土木工程学院, 河南郑州 451191;
2. 天津师范大学天津市地理空间信息技术工程中心, 天津 300387;
3. 湖南大学电气与信息工程学院, 湖南长沙 410082

收稿日期:2020-03-12 修回日期:2020-05-07 出版日期:2020-10-25 发布日期:2020-10-29
作者简介:王果(1986-),男,博士,讲师,主要从事三维数据获取及处理方面的研究工作。E-mail:wg@haue.edu.cn
基金资助:
国家自然科学基金（42001412）；广西重点研发计划（桂科AB18050014）；河南省科技攻关计划项目（202102310333）；河南省高等学校重点科研项目（18B170003）；河南工程学院博士基金（D2015040）

Method of building extraction from UAV oblique photography point cloud based on cloth simulation

WANG Guo¹, WANG Qiang², LIU Shaotang¹, YANG Fuqin¹, ZHAO Guangxing¹, YANG Bin³

1. Institute of Civil Engineering, Henan University of Engineering, Zhengzhou 451191, China;
2. Tianjin Geospatial Information Technology Engineering Centre, Tianjin Normal University, Tianjin 300387, China;
3. School of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Received:2020-03-12 Revised:2020-05-07 Online:2020-10-25 Published:2020-10-29

摘要/Abstract

摘要： 受布料模拟滤波思想的启发，本文提出一种基于无人机倾斜摄影密集匹配点云的建筑提取新方法。该方法引入布料模拟进行建筑顶面的初步识别，通过模拟布料下落过程，分析布料与对应密集匹配点云之间的作用，确定布料由重力下降后所停留的位置作为建筑顶面的初步识别，然后通过密度聚类算法进行建筑区分，从而实现建筑物顶面的单体化提取。通过实测数据进行试验，结果表明，该方法能取得较好的效果，为基于密集匹配点云的建筑物提取提供一种新思路。

关键词: 无人机倾斜摄影, 密集匹配点云, 布料模拟, 密度聚类, 建筑提取

Abstract: Inspired by the idea of cloth simulation filtering, this paper presents a new method of building extraction from dense matching point cloud based on UAV oblique photography. The method introduces cloth simulation to identify the top of the building as the first step. By simulating the falling process of cloth, the function between cloth and corresponding dense matching point cloud is analyzed, and the position where cloth stays after gravity falling is determined as the building top. And then buildings are distinguished by the density clustering algorithm so as to realize the monomer extraction of the building top surface. The experimental results show that the method can achieve better results and provide a new idea for building extraction from dense matching point cloud based on UAV oblique photography.

Key words: UAV based oblique photography, dense matching point cloud, cloth simulation, density clustering, building extraction

中图分类号:

王果, 王强, 刘绍堂, 杨福芹, 赵光兴, 杨彬. 布料模拟法无人机倾斜摄影建筑点云提取[J]. 测绘通报, 2020, 0(10): 97-100.

WANG Guo, WANG Qiang, LIU Shaotang, YANG Fuqin, ZHAO Guangxing, YANG Bin. Method of building extraction from UAV oblique photography point cloud based on cloth simulation[J]. Bulletin of Surveying and Mapping, 2020, 0(10): 97-100.

参考文献

[1] 桑文刚,李娜,韩峰,等.小区域消费级无人机倾斜摄影像控点布设及建模精度研究[J].测绘通报,2019(10):93-96.
[2] 王果,蒋瑞波,肖海红,等.基于无人机倾斜摄影的露天矿边坡三维重建[J].中国矿业,2017,26(4):158-161.
[3] 杨必胜,董震.点云智能研究进展与趋势[J].测绘学报,2019,48(12):1575-1585.
[4] 任诚,高利敏,冯耀楼,等.基于无人机倾斜摄影的建筑物三维建模尝试[J].测绘通报,2019(2):161-164.
[5] DAHLKE D,LINKIEWICZ M.Comparison between two generic 3D building reconstruction algorithms:point cloud based vs. image processing based[C]//International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Prague:International Society of Photogrammetry and Remote Sensing,2016.
[6] 冯帅.影像匹配点云与机载激光点云的比较[J].地理空间信息,2014,12(6):82-83.
[7] MALTEZOS E,KYRKOU A,IOANNIDIS C.LiDAR vs dense image matching point clouds in complex urban scenes[C]//Fourth International Conference on Remote Sensing and Geoinformation of the Environment. Paphos:Cyprus Remote Sensing Society,2016.
[8] 闫利,魏峰.利用密集匹配点云的建筑单体提取算法研究[J].中国激光,2018,45(7):270-277.
[9] AWRANGJEB M,LU G,FRASER C. Automatic building extraction from LiDAR data covering complex urban scenes[C]//International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Zurich:International Society of Photogrammetry and Remote Sensing,2014.
[10] NOVACHEVA A. Building roof reconstruction from LiDAR data and aerial images through plane extraction and color edge detection[C]//International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Beijing:International Society of Photogrammetry and Remote Sensing,2008.
[11] 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.
[12] 赵宗泽,张永军.基于植被指数限制分水岭算法的机载激光点云建筑物提取[J].光学学报,2016,36(10):503-511.
[13] LI M L, NAN L L, SMITH N, et al. Reconstructing building mass models from UAV images[J]. Computers & Graphics, 2016, 54(2):84-93.
[14] ZHANG W M, QI J B, WAN P, et al. An easy-to-use airborne LiDAR data filtering method based on cloth simulation[J]. Remote Sensing, 2016, 8(6):501.
[15] 曲金博,王岩,赵琪.DBSCAN聚类和改进的双边滤波算法在点云去噪中的应用[J].测绘通报,2019(11):89-92.
[16] 袁德宝,王炳灵,闫瑜,等.室内位置轨迹的聚类与可视化[J].测绘通报,2019(5):21-24.
[17] 王果,谢瑞,肖海红,等. 无人机倾斜摄影技术支持下的校园三维模型构建[J].河南工程学院学报(自然科学版), 2017, 29(1):44-47.
[18] LIN Zongjian, XIE Feifei, SU Guozhong. Accuracy analysis of low altitude photogrammetry with wide-angle camera[J]. Journal of Geodesy and Geoinformation Science, 2018, 1(1):30-38.

布料模拟法无人机倾斜摄影建筑点云提取

Method of building extraction from UAV oblique photography point cloud based on cloth simulation

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 10

编辑推荐

Metrics

本文评价

[1]	王艳军, 林云浩, 王书涵, 李少春, 王孟杰. OSM辅助车载LiDAR点云三维道路边界精细提取[J]. 测绘通报, 2022, 0(7): 18-25.
[2]	李少先. 利用双向布料模拟的机载建筑物点云提取[J]. 测绘通报, 2022, 0(3): 148-151.
[3]	石壮, 杜全叶, 王庆栋, 马东岭, 崔琰. 虚拟格网分类支持下的密集匹配点云布料模拟滤波[J]. 测绘通报, 2022, 0(2): 73-77.
[4]	高智梅, 王竞雪, 沈昭宇. 机载LiDAR建筑物点云渐进提取算法[J]. 测绘通报, 2021, 0(8): 7-13,36.
[5]	付翔翔, 邓运员, 郑文武, 周邵宁, 周佳露. 基于无人机影像密集匹配点云的传统村落地面点提取及DEM生成——以湘西德夯村为例[J]. 测绘通报, 2021, 0(12): 1-5.
[6]	王燕锋, 盛业华, 秦佳睿, 张思阳, 闵祥强. 单体建筑物点云数据的CSF净化处理[J]. 测绘通报, 2020, 0(9): 72-75,84.
[7]	原明超, 仇俊. 无人机倾斜摄影测量在三维模型测图中的应用[J]. 测绘通报, 2020, 0(7): 116-119,142.
[8]	张晓庆, 胡辉辉, 王治中, 杜耀, 杨海波. 水上水下一体化三维河道场景构建与展示[J]. 测绘通报, 2020, 0(12): 118-121.
[9]	桑文刚, 李娜, 韩峰, 赵培华, 李玉斌. 小区域消费级无人机倾斜摄影像控点布设及建模精度研究[J]. 测绘通报, 2019, 0(10): 93-96.
[10]	陈宇, 徐青, 姚富山, 施群山, 吕亮, 卢万杰. 影像密集匹配点云的单体化提取[J]. 测绘通报, 2016, 0(12): 51-55.