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Dense Structure Inference for Object Classification in Aerial LIDAR Dataset
2010
2010 20th International Conference on Pattern Recognition
We present a framework to classify small freeform objects in 3D aerial scans of a large urban area. The system first identifies large structures such as the ground surface and roofs of buildings densely built in the scene, by fitting planar patches and grouping adjacent patches similar in pose together. Then, it segments initial object candidates which represent the visible surface of an object using the identified structures. To deal with sparse density in points representing each candidate,
doi:10.1109/icpr.2010.747
dblp:conf/icpr/KimM10
fatcat:wbibv23ktrbzlkeynblsvuw4cu