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Proceedings Paper

Feature-constrained surface reconstruction approach for point cloud data acquired with 3D laser scanner
Author(s): Yongbo Wang; Yehua Sheng; Guonian Lu; Peng Tian; Kai Zhang
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Paper Abstract

Surface reconstruction is an important task in the field of 3d-GIS, computer aided design and computer graphics (CAD & CG), virtual simulation and so on. Based on available incremental surface reconstruction methods, a feature-constrained surface reconstruction approach for point cloud is presented. Firstly features are extracted from point cloud under the rules of curvature extremes and minimum spanning tree. By projecting local sample points to the fitted tangent planes and using extracted features to guide and constrain the process of local triangulation and surface propagation, topological relationship among sample points can be achieved. For the constructed models, a process named consistent normal adjustment and regularization is adopted to adjust normal of each face so that the correct surface model is achieved. Experiments show that the presented approach inherits the convenient implementation and high efficiency of traditional incremental surface reconstruction method, meanwhile, it avoids improper propagation of normal across sharp edges, which means the applicability of incremental surface reconstruction is greatly improved. Above all, appropriate k-neighborhood can help to recognize un-sufficient sampled areas and boundary parts, the presented approach can be used to reconstruct both open and close surfaces without additional interference.

Paper Details

Date Published: 29 April 2008
PDF: 12 pages
Proc. SPIE 7000, Optical and Digital Image Processing, 700021 (29 April 2008); doi: 10.1117/12.780539
Show Author Affiliations
Yongbo Wang, Nanjing Normal Univ. (China)
Yehua Sheng, Nanjing Normal Univ. (China)
Guonian Lu, Nanjing Normal Univ. (China)
Peng Tian, Nanjing Normal Univ. (China)
Kai Zhang, Nanjing Normal Univ. (China)


Published in SPIE Proceedings Vol. 7000:
Optical and Digital Image Processing
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet, Editor(s)

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