3D Building Model Reconstruction from Multi-view Aerial Imagery and Lidar Data
A novel approach by integrating multi-view aerial imagery and lidar data is proposed to reconstruct 3D building models with accurate geometric position and fine details. First, a new algorithm is introduced for determination of principal orientations of a building, thus benefiting to improve the correctness and robustness of boundary segment extraction in aerial imagery. A new dynamic selection strategy based on lidar point density analysis and K-means clustering is then proposed to identify boundary segments from non-boundary segments. Second, 3D boundary segments are determined by incorporating lidar data and the 2D segments extracted from multi-view imagery. Finally, a new strategy for 3D building model reconstruction including automatic recovery of lost boundaries and robust reconstruction of rooftop patches is introduced. The experimental results indicate that the proposed approach can provide high quality 3D models with high-correctness, high-completeness, and good geometric accuracy.
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Document Type: Research Article
Publication date: February 1, 2011
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- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies.
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