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HIERARCHICAL HIGHER ORDER CRF FOR THE CLASSIFICATION OF AIRBORNE LIDAR POINT CLOUDS IN URBAN AREAS
2016
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
We propose a novel hierarchical approach for the classification of airborne 3D lidar points. Spatial and semantic context is incorporated via a two-layer Conditional Random Field (CRF). The first layer operates on a point level and utilises higher order cliques. Segments are generated from the labelling obtained in this way. They are the entities of the second layer, which incorporates larger scale context. The classification result of the segments is introduced as an energy term for the next
doi:10.5194/isprs-archives-xli-b3-655-2016
fatcat:g33xs63sgfeb5i7hwur2kc4u44