In this investigation, we address the task of airborne LiDAR point cloud labelling for urban areas by presenting a contextual classification methodology based on a Conditional Random Field (CRF). A two-stage CRF is set up: ...

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 ...

Feature fusion of remote sensing images and LiDAR points cloud data, which have strong complementarity, can effectively play the advantages of multi-class features to provide more reliable information support for the remote ...

This paper proposes a two-layer Conditional Random Field model for simultaneous classification of land cover and land use. Both classification tasks are integrated into a unified graphical model, which is reasonable due ...