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Planar segmentation from point clouds via graph Laplacian regularized K-planes
Wei Sui; Lingfeng Wang; Huaiyu Wu; Chunhong Pan
Conference NameAsian Conference on Pattern Recognition
Source PublicationAsian Conference on Pattern Recognition (ACPR)
Conference Date5-8 Nov. 2013
Conference PlaceNaha
Project Number61075016 ; 61203277 ; 61272049 ; 61272331

Extracting planar surfaces from 3D point clouds is an important and challenging step for generating building models as the obtained data are always noisy, missing and unorganised. In this paper, we present a novel graph Laplacian regularized K-planes method for segmenting piece-wise planar surfaces of urban building point clouds. The core ideas behind our model are from two aspects: 1) a linear projection model is utilized to fit planar surfaces globally; 2) a graph Laplacian regularization is applied to preserve smoothness of each plane locally. The two terms are combined as an objective function, which is minimized via an iterative updating algorithm. Comparative experiments on both synthetic and real data sets are performed. The results demonstrate the effectiveness and efficiency of our method.

KeywordSegmentation Piece-wise Planar Surfaces Graph Laplacian Point Clouds
Indexed ByEI
Funding ProjectThe National Natural Science Foundation of China under Grants
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Document Type会议论文
Corresponding AuthorWei Sui
AffiliationThe National Laboratory of Pattern Recognition (NLPR) , Institute of Automation, ChineseAcademy of Sciences
Recommended Citation
GB/T 7714
Wei Sui,Lingfeng Wang,Huaiyu Wu,et al. Planar segmentation from point clouds via graph Laplacian regularized K-planes[C]:IEEE,2013:64-68.
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