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    王震等:A Local Structure and Direction-Aware Optimization Approach for Three-Dimensional Tree Modeling

    作者:来源:发布时间:2016-10-14
    A Local Structure and Direction-Aware Optimization Approach for Three-Dimensional Tree Modeling
    作者:Wang, Z (Wang, Zhen)[ 1,2 ] ; Zhang, LQ (Zhang, Liqiang)[ 1 ] ; Fang, T (Fang, Tian)[ 3 ] ; Tong, XH (Tong, Xiaohua)[ 4 ] ; Mathiopoulos, PT (Mathiopoulos, P. Takis)[ 5 ] ; Zhang, L (Zhang, Liang)[ 1 ] ; Mei, J (Mei, Jie)[ 1 ]
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
    卷: 54  期: 8  页: 4749-4757
    DOI: 10.1109/TGRS.2016.2551286
    出版年: AUG 2016
    摘要
    Modeling 3-D trees from terrestrial laser scanning (TLS) point clouds remains a challenging task for several well-known reasons, including their complex structure and severe occlusions. In order to accurately reconstruct 3-D tree models from TLS point clouds that typically suffer from significant occlusions, in this paper, a novel local structure and direction-aware approach is presented to successfully complete missing structures of trees. In this method, we first extract the coarse tree skeleton from the input point cloud, and thus, the branch dominant direction and the point density of each branch are obtained. By a skeleton-based Laplacian algorithm, the point cloud is further shrunk into a skeleton point cloud to highlight the branch dominant direction of each branch. For obtaining even more accurate point densities, a dictionary-based algorithm is utilized to learn and reconstruct the local structure. Finally, the branch dominant direction and point density are integrated into an iterative optimization process to recover the missing data. Extensive experimental results have shown that the proposed method is very robust to incomplete data sets, and it is capable of accurately reconstructing 3-D trees, which are partially, or even to a large extent, missing from the input point cloud.
    通讯作者地址: Wang, Z (通讯作者)
    Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.
    通讯作者地址: Wang, Z (通讯作者)
    China Univ Geosci, Dept Geoinformat, Beijing 100083, Peoples R China.
    地址:
    [ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
    [ 2 ] China Univ Geosci, Dept Geoinformat, Beijing 100083, Peoples R China
    [ 3 ] Hong Kong Univ Sci & Technol, Kowloon, Hong Kong, Peoples R China
    [ 4 ] Tongji Univ, Sch Surveying & Geoinformat, Shanghai 200092, Peoples R China
    [ 5 ] Univ Athens, Dept Informat & Telecommun, Athens 15784, Greece
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