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RISS 인기검색어
- 검색키워드
- 저자 : Jiben Yang (검색결과 2 건)
- 무료
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- 유료
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Automatic Extraction Method of Urban Road Curb Boundary from Vehicle-borne Laser Point Clouds
Hongwei Ren,Rufei Liu,Fei Wang,Jiben Yang 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.8
With the acceleration of urbanization, urban road networks are being extended and updated at an alarming rate. How to extract the boundary information of the urban road network efficiently and scientifically to support fine urban management has become a difficult problem. Vehicle-Borne Mobile Mapping System can quickly and efficiently obtain 3D road data, and further realize the extraction of urban road boundary. Based on the tracking information of the Vehicle-Borne Mobile Mapping System, this paper extracts contiguous laser scanning lines from vehicle-borne mobile laser scanning data. By further analyzing the spatial geometric distribution features of the point clouds on different terrain of scan lines, this paper proposes an adaptive window clustering classification method based on the scan line index to solve the problem of the automatic extraction of urban road curb boundary. Experiments are carried out on two point clouds data obtained by the vehicle-borne mobile measurement system. And the accuracy of the extraction of curbs boundary is 99%. The experiment results show that this method can effectively reduce the interference of road noise points as well as the influence of facade features on the boundary extraction of curbs and adapt to different shapes and distribution conditions of urban roads curbs.
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Bori Cong,Qingying Li,Rufei Liu,Fei Wang,Danyang Zhu,Jiben Yang 대한토목학회 2022 KSCE Journal of Civil Engineering Vol.26 No.12
Mobile laser scanning can quickly and dynamically obtain a wide range of urban scene point clouds. However, due to factors such as occlusion and field of view limitation, it needs to be supplemented by terrestrial laser scanning. The acquisition methods and data quality of mobile point clouds and terrestrial point clouds are quite different, the target of urban scene point clouds is complex and diverse, and the corresponding feature is difficult to extract, so the point cloud fusion is difficult. To this end, a point cloud registration method of mobile and terrestrial scanning based on the target features of artificial ground objects is proposed. Firstly, the data features of mobile laser scanning point clouds and terrestrial laser scanning point clouds are analyzed, and the point clouds are diluted with equal density. Then, the artificial ground objects are extracted as the registration primitives to reduce the scene complexity, and the features of urban scenes and the features of point cloud eigenvalues and principal curvature attributes are analyzed. Combined with the octree voxel index, the multi-scale key point extraction method is constructed to extract the multi-scale key points of registration primitives. Finally, the key point constraint is used to improve the deficiencies of 4PCS (4-Points Congruent Sets) algorithm and ICP (Iterative Closest Point) algorithm to complete the registration of mobile and terrestrial point clouds in different road scenes. Experiments show that the point cloud registration accuracy can reach 2.6 cm, which provides a feasible method for high precision fusion of multi-platform laser point clouds.
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