Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 425-432, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/425/2016/
doi:10.5194/isprs-archives-XLI-B3-425-2016
 
09 Jun 2016
EXTENSION OF RCC TOPOLOGICAL RELATIONS FOR 3D COMPLEX OBJECTS COMPONENTS EXTRACTED FROM 3D LIDAR POINT CLOUDS
Xu-Feng Xing, Mir Abolfazl Mostafavia, and Chen Wang Dept. of Geomatics, Laval University, Québec, Canada
Keywords: Topological relations, planar regions, components, automatic 3D modelling, point cloud Abstract. Topological relations are fundamental for qualitative description, querying and analysis of a 3D scene. Although topological relations for 2D objects have been extensively studied and implemented in GIS applications, their direct extension to 3D is very challenging and they cannot be directly applied to represent relations between components of complex 3D objects represented by 3D B-Rep models in R3. Herein we present an extended Region Connection Calculus (RCC) model to express and formalize topological relations between planar regions for creating 3D model represented by Boundary Representation model in R3. We proposed a new dimension extended 9-Intersection model to represent the basic relations among components of a complex object, including disjoint, meet and intersect. The last element in 3*3 matrix records the details of connection through the common parts of two regions and the intersecting line of two planes. Additionally, this model can deal with the case of planar regions with holes. Finally, the geometric information is transformed into a list of strings consisting of topological relations between two planar regions and detailed connection information. The experiments show that the proposed approach helps to identify topological relations of planar segments of point cloud automatically.
Conference paper (PDF, 1331 KB)


Citation: Xing, X.-F., Mostafavia, M. A., and Wang, C.: EXTENSION OF RCC TOPOLOGICAL RELATIONS FOR 3D COMPLEX OBJECTS COMPONENTS EXTRACTED FROM 3D LIDAR POINT CLOUDS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 425-432, doi:10.5194/isprs-archives-XLI-B3-425-2016, 2016.

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