Article thumbnail

Place recognition using surface entropy features

By T. Fiolka, J. Stückler, D.A. Klein, D. Schulz and S. Behnke

Abstract

In this paper, we present an interest point detector and descriptor for 3D point clouds and depth images, coined SURE, and use it for recognizing semantically distinct places in indoor environments. We propose an interest operator that selects distinctive points on surfaces by measuring the variation in surface orientation based on surface normals in the local vicinity of a point. Furthermore, we design a view-poseinvariant 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). Our descriptor achieves superior results for matching interest points between images and also requires lower computation time. Finally, we evaluate the use of SURE features for recognizing places

Year: 2012
OAI identifier: oai:fraunhofer.de:N-237684
Provided by: Fraunhofer-ePrints
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://publica.fraunhofer.de/d... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.