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http://dx.doi.org/10.7848/ksgpc.2012.30.1.001

Automatic 3D Object Digitizing and Its Accuracy Using Point Cloud Data  

Yoo, Eun-Jin (세종대학교 지구정보공학과)
Yun, Seong-Goo (세종대학교 지구정보공학과)
Lee, Dong-Cheon (세종대학교 지구정보공학과)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.30, no.1, 2012 , pp. 1-10 More about this Journal
Abstract
Recent spatial information technology has brought innovative improvement in both efficiency and accuracy. Especially, airborne LiDAR system(ALS) is one of the practical sensors to obtain 3D spatial information. Constructing reliable 3D spatial data infrastructure is world wide issue and most of the significant tasks involved with modeling manmade objects. This study aims to create a test data set for developing automatic building modeling methods by simulating point cloud data. The data simulates various roof types including gable, pyramid, dome, and combined polyhedron shapes. In this study, a robust bottom-up method to segment surface patches was proposed for generating building models automatically by determining model key points of the objects. The results show that building roofs composed of the segmented patches could be modeled by appropriate mathematical functions and the model key points. Thus, 3D digitizing man made objects could be automated for digital mapping purpose.
Keywords
3D point cloud data; Segmentation; Digital mapping; DBM;
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