Welcome! This is an implementation of the Kobyshev score from the 3DV 2016 paper. This is only the initial score, the refined score code is pending... 3D Saliency for Finding Landmark Buildings, 3DV 2016 N. Kobyshev, H. Riemenschneider, A. Bodis-Szomoru, L. Van Gool http://varcity.eu/publication.html The code takes a 3D pointcloud (.ply) and calculates the Kobyshev score as described in Eq. 2 to measure the 3D saliency. The output are the KNNs, the score, a visualization and the features. /// requirements PCL v1.7 OMP [optional] /// compile.sh mkdir build cd build cmake .. make -j8 /// run.sh build/landmarkness ../data/fraumunster.ply /// example output: Reading ../data/fraumunster.ply Loaded 405575 points. Execution time: 0.0643783 computing normals... done recting 405575 normal directions Execution time: 0.50857 computing FPFH... done compusting 405575 feature descriptors Execution time: 48.2682 computing knn neighbors Execution time: 2.38485 done measuring 20278750 neighbors (avg=50) landmark min=-3.91202 max=0 Execution time: 259.573 computing visualization cloud Execution time: 2.09063 ka-pow!