This tool computes the Mean Map Entropy and the Mean Plane Variance of a point cloud.
Furthermore a pointcloud is generated that encodes the Map Entropy and Plane Variance in each point.
Use the point cloud viewer of your choice to visualize these measures (e.g. pcl_viewer).
mkdir build
cd build
cmake ..
make
./mean_map_entropy path/to/pointcloud.pcd [-stepsize int] [-radius double] [-punishSolitaryPoints] [-minNeighbors int]
- stepsize: stepsize used iterating through the pointcloud (default: 1)
- radius: radius used for search for neighboring points (default: 0.3)
- punishSolitaryPoints: punishes points with bad values where the number of neighbors is under minNeighbors (default: false)
- minNeighbors: threshold (default: 15)
Please cite our paper if you use this tool. Razlaw, J., Droeschel, D., Holz, D., & Behnke, S. (2015, September). [Evaluation of registration methods for sparse 3D laser scans][1]. In Mobile Robots (ECMR), 2015 European Conference on (pp. 1-7). IEEE. [1]: http://www.ais.uni-bonn.de/papers/ECMR_2015_Razlaw.pdf