Robust and effective airborne lidar point cloud classification based on hybrid features

HIGHLIGHTS

  • who: L. F. Liaoa et al. from the XXIV ISPRS Congress (, edition), June, Nice, France have published the research: ROBUST AND EFFECTIVE AIRBORNE LIDAR POINT CLOUD CLASSIFICATION BASED ON HYBRID FEATURES, in the Journal: (JOURNAL)
  • what: The authors propose a robust and effective point cloud classification approach that integrates point cloud supervoxels and their locally convex connected patches into a random forest classifier. The most basic requirement for these applications is the semantic classification of 3D point cloud data, which has been a research focus among photogrammetry and remote sensing communities.

SUMMARY

     

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