LiDAR Segmentation using Suitable Seed Points for 3D Building Extraction
نویسندگان
چکیده
منابع مشابه
Building Extraction Using Lidar Data
Accurate 3D surface models in urban areas are essential for a variety of applications, such as visualization, GIS, and mobile communications. Since manual surface reconstruction is very costly and time consuming, the development of automated algorithms is of great importance. On the other hand LIDAR data is a relatively new technology for obtaining Digital Surface Models (DSM) of the earth’s su...
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The objective of segmentation on point clouds is to spatially group points with similar properties into homogeneous regions. Segmentation is a fundamental issue in processing point clouds data acquired by LiDAR and the quality of segmentation largely determines the success of information retrieval. Unlike the image or TIN model, the point clouds do not explicitly represent topology information....
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This paper presents a new LiDAR segmentation technique for automatic extraction of building roofs. First, it uses a height threshold, based on the digital elevation model to divide the LiDAR point cloud into ‘ground’ and ‘non-ground’ points. Then starting from the maximum LiDAR height, and decreasing the height at each iteration, it looks for coplanar points to form planar roof segments. At eac...
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Introduction Work Flow DTM Generation Building Detection Building Reconstruction Conclusion and Future Work References Building Extraction from LIDAR Data Franz Rottensteiner and Christian Briese
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ژورنال
عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2014
ISSN: 2194-9034
DOI: 10.5194/isprsarchives-xl-3-1-2014