Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W19, 209-214, 2011
https://doi.org/10.5194/isprsarchives-XXXVIII-4-W19-209-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
07 Sep 2012
CONDITIONAL RANDOM FIELDS FOR THE CLASSIFICATION OF LIDAR POINT CLOUDS
J. Niemeyer1, C. Mallet2, F. Rottensteiner1, and U. Sörgel1 1Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, D-30167 Hannover, Germany
2Université Paris Est, Laboratoire MATIS, Institut Géographique National, F-94165 Saint-Mandé, France
Keywords: Conditional Random Fields, 3D Point Cloud, LiDAR, Classification Abstract. In this paper we propose a probabilistic supervised classification algorithm for LiDAR (Light Detection And Ranging) point clouds. Several object classes (i.e. ground, building and vegetation) can be separated reliably by considering each point's neighbourhood. Based on Conditional Random Fields (CRF) this contextual information can be incorporated into classification process in order to improve results. Since we want to perform a point-wise classification, no primarily segmentation is needed. Therefore, each 3D point is regarded as a graph's node, whereas edges represent links to the nearest neighbours. Both nodes and edges are associated with features and have effect on the classification. We use some features available from full waveform technology such as amplitude, echo width and number of echoes as well as some extracted geometrical features. The aim of the paper is to describe the CRF model set-up for irregular point clouds, present the features used for classification, and to discuss some results. The resulting overall accuracy is about 94 %.
Conference paper (PDF, 1411 KB)


Citation: Niemeyer, J., Mallet, C., Rottensteiner, F., and Sörgel, U.: CONDITIONAL RANDOM FIELDS FOR THE CLASSIFICATION OF LIDAR POINT CLOUDS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-4/W19, 209-214, https://doi.org/10.5194/isprsarchives-XXXVIII-4-W19-209-2011, 2011.

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