2.5D Dual Contouring: A Robust Approach to Creating Building Models from Aerial LiDAR Point Clouds

被引:0
|
作者
Zhou, Qian-Yi [1 ]
Neumann, Ulrich [1 ]
机构
[1] Univ So Calif, Los Angeles, CA 90089 USA
来源
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a robust approach to creating 2.5D building models from aerial LiDAR point clouds. The method is guaranteed to produce crack-free models composed of complex roofs and vertical walls connecting them. By extending classic dual contouring into a 2.5D method, we achieve a simultaneous optimization over the three dimensional surfaces and the two dimensional boundaries of roof layers. Thus, our method can generate building models with arbitrarily shaped roofs while keeping the verticality of connecting walls. An adaptive grid is introduced to simplify model geometry in an accurate manner. Sharp features are detected and preserved by a novel and efficient algorithm.
引用
收藏
页码:115 / 128
页数:14
相关论文
共 49 条
  • [1] 3D BUILDING RECONSTRUCTION FROM LIDAR POINT CLOUDS BY ADAPTIVE DUAL CONTOURING
    Orthuber, E.
    Avbelj, J.
    PIA15+HRIGI15 - JOINT ISPRS CONFERENCE, VOL. II, 2015, 2-3 (W4): : 157 - 164
  • [2] Aerial 3D Building Detection and Modeling From Airborne LiDAR Point Clouds
    Sun, Shaohui
    Salvaggio, Carl
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (03) : 1440 - 1449
  • [3] Investigation on Roof Segmentation for 3D Building Reconstruction from Aerial LIDAR Point Clouds
    Albano, Raffaele
    APPLIED SCIENCES-BASEL, 2019, 9 (21):
  • [4] Segmentation and Reconstruction of Polyhedral Building Roofs From Aerial Lidar Point Clouds
    Sampath, Aparajithan
    Shan, Jie
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (03): : 1554 - 1567
  • [5] PBWR: Parametric-Building-Wireframe Reconstruction from Aerial LiDAR Point Clouds
    Huang, Shangfeng
    Wang, Ruisheng
    Guo, Bo
    Yang, Hongxin
    2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2024, : 27778 - 27787
  • [6] 3D building change detection by combining LiDAR point clouds and aerial imagery
    Peng, Daifeng
    Zhang, Yongjun
    Xiong, Xiaodong
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2015, 40 (04): : 462 - 468
  • [7] Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
    Lafarge, Florent
    Mallet, Clement
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2012, 99 (01) : 69 - 85
  • [8] Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
    Florent Lafarge
    Clément Mallet
    International Journal of Computer Vision, 2012, 99 : 69 - 85
  • [9] Improved GAC Model for automatic building extraction from LiDAR point clouds and aerial image
    Sun, Ying
    Zhang, Xinchang
    Kang, Tingjun
    Zhao, Xiaoyang
    Zhang, Wei
    Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2013, 42 (03): : 337 - 343
  • [10] Creating 3D city models with building footprints and LIDAR point cloud classification: A machine learning approach
    Park, Yujin
    Guldmann, Jean-Michel
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2019, 75 : 76 - 89