Abstract
We present a pipeline to reconstruct complete geometry of architectural buildings from point clouds obtained by sparse range laser scanning. Due to limited accessibility of outdoor environments, complete and sufficient scanning of every face of an architectural building is often impossible. Our pipeline deals with architectures that are made of planar faces and faithfully constructs a polyhedron of low complexity based on the incomplete scans. The pipeline first recognizes planar regions based on point clouds, then proceeds to compute plane intersections and corners (in this paper, we use the informal terms corner or vertex corner to stand for a polyhedron vertex. See the Overview section for notation declarations), and finally produces a complete polyhedron. Within the pipeline, several algorithms based on the polyhedron geometry assumption are designed to perform data clustering, boundary detection, and face extraction. Our system offers a convenient user interface but minimizes the necessity of user intervention. We demonstrate the capability and advantage of our system by modeling real-life buildings.
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This work is dedicated to the Minnesota 3D scanning project conducted at the University of Minnesota, Twin Cities. For more information, please refer to the project website http://www.cs.umn.edu/~baoquan/scan.html.
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Chen, J., Chen, B. Architectural Modeling from Sparsely Scanned Range Data. Int J Comput Vis 78, 223–236 (2008). https://doi.org/10.1007/s11263-007-0105-5
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DOI: https://doi.org/10.1007/s11263-007-0105-5