Automatic building extraction and segmentation directly from lidar point clouds

Jingjue Jiang; Ying Ming

doi:10.1117/12.713262

28 October 2006 Automatic building extraction and segmentation directly from lidar point clouds

Jingjue Jiang, Ying Ming

Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64191O (2006) https://doi.org/10.1117/12.713262
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

This paper presents an automatic approach for building extraction and segmentation directly from Lidar point clouds without previous rasterization or triangulation. The algorithm works in the following sequential steps. First, a filtering algorithm, which is capable of preserving steep terrain features, is performed on raw Lidar point clouds. Points that belong to the bare earth and those that belong to buildings are separated. Second, the building points which may include some vegetation and other objects due to the disturbance of noise and the distribution of points are segmented further by using a Riemannian Graph. Then building segments are recognized by considering size and roughness. Finally, each segment can be treated as a building roof plane. Experiment results show that the algorithm is very promising.

Citation Download Citation

Jingjue Jiang and Ying Ming "Automatic building extraction and segmentation directly from lidar point clouds", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191O (28 October 2006); https://doi.org/10.1117/12.713262

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