Building roof contour extraction from LiDAR data
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This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.
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Building roof contours , DSM , Markov random field , Simulated annealing , Automatic extraction , Building roof , Contour Extraction , Digital surface models , Energy functions , LIDAR data , Markov Random Fields , Polygonization , Region-merging , Spatial constraints , Splitting techniques , Vectorization , Optical radar , Photogrammetry , Remote sensing , Roofs , Buildings
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American Society for Photogrammetry and Remote Sensing Annual Conference 2011, p. 88-92.
