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http://dx.doi.org/10.7848/ksgpc.2016.34.3.243

Curved Feature Modeling and Accuracy Analysis Using Point Cloud Data  

Lee, Dae Geon (Department of Geoinformation Engineering, Sejong University)
Yoo, Eun Jin (Department of Geoinformation Engineering, Sejong University)
Lee, Dong-Cheon (Department of Geoinformation Engineering, Sejong University)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.34, no.3, 2016 , pp. 243-251 More about this Journal
Abstract
LiDAR data processing steps include noise removal, filtering, classification, segmentation, shape recognition, modeling, and quality assessment. This paper focuses on modeling and accuracy evaluation of 3D objects with curved surfaces. The appropriate modeling functions were determined by analyzing surface patch shape. Existing methods for modeling curved surface features require linearization, initial approximation, and iteration of the non-linear functions. However, proposed method could directly estimate the unknown parameters of the modeling functions. The results demonstrate feasibility of the proposed method. The proposed method was applied to the simulated and real building data of hemi-spherical and semi-cylindrical surfaces. The parameters and accuracy of the modeling functions were estimated. It is expected that the proposed method would contribute to automatic modeling of various objects.
Keywords
Laser Scanner; Point Clouds; Geometric Surfaces; Surface Functions; Modeling Accuracy;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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