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Point feature extraction on 3D range scans taking into account object boundaries

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4 Author(s)
Bastian Steder ; Dept. of Computer Science of the University of Freiburg, Germany ; Radu Bogdan Rusu ; Kurt Konolige ; Wolfram Burgard

In this paper we address the topic of feature extraction in 3D point cloud data for object recognition and pose identification. We present a novel interest keypoint extraction method that operates on range images generated from arbitrary 3D point clouds, which explicitly considers the borders of the objects identified by transitions from foreground to background. We furthermore present a feature descriptor that takes the same information into account. We have implemented our approach and present rigorous experiments in which we analyze the individual components with respect to their repeatability and matching capabilities and evaluate the usefulness for point feature based object detection methods.

Published in:

Robotics and Automation (ICRA), 2011 IEEE International Conference on

Date of Conference:

9-13 May 2011