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http://dx.doi.org/10.7780/kjrs.2011.27.2.121

Reconstruction of 3D Building Model from Satellite Imagery Based on the Grouping of 3D Line Segments Using Centroid Neural Network  

Woo, Dong-Min (Department of Electronics Engineering, Myongji University)
Park, Dong-Chul (Department of Electronics Engineering, Myongji University)
Ho, Hai-Nguyen (Department of Electronics Engineering, Myongji University)
Kim, Tae-Hyun (Department of Electronics Engineering, Myongji University)
Publication Information
Korean Journal of Remote Sensing / v.27, no.2, 2011 , pp. 121-130 More about this Journal
Abstract
This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.
Keywords
3D line; satellite image; centroid neural network; DEM; rooftop model; grouping;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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