Distinctive 3D surface entropy features for place recognition

In this paper, we present a variant of SURE, an interest point detector and descriptor for 3D point clouds and depth images and use it for recognizing semantically distinct places in indoor environments. The SURE interest operator selects distinctive points on surfaces by measuring the variation in surface orientation based on surface normals in the local vicinity of a point. Furthermore SURE includes a view-pose-invariant descriptor that captures local surface properties and incorporates colored texture information. In experiments, we compare our approach to a state-of-the-art feature detector in depth images (NARF). Finally, we evaluate the use of SURE features for recognizing places and demonstrate its advantages.