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Adding rotational robustness to the surface-approximation polynomials descriptor

: Bormann, Richard; Fischer, Jan; Arbeiter, Georg; Verl, Alexander

Preprint urn:nbn:de:0011-n-2252896 (3.4 MByte PDF)
MD5 Fingerprint: fdf02894737d027161c6f3e082aa6d04
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Created on: 17.1.2013

Iwata, Hiroyasu (Ed.) ; IEEE Robotics and Automation Society; Institute of Electrical and Electronics Engineers -IEEE-:
Humanoids 2012, 12th International IEEE-RAS International Conference on Humanoid Robots : November 29-December 1, 2012, Osaka, Japan; Humanoids and Humans: Towards A New Frontier
New York, NY: IEEE, 2012
ISBN: 978-1-4673-1368-1
ISBN: 978-1-4673-1369-8
International Conference on Humanoid Robots (Humanoids) <12, 2012, Osaka>
Conference Paper, Electronic Publication
Fraunhofer IPA ()
surface; approximation; Datenmanagement; object classification; machine vision; maschinelles Sehen; Oberfläche; Objekterkennung; Roboter; Kamera

The Surface-Approximation Polynomials (SAP) descriptor has been shown to be an appropriate global surface edscriptor for object categorization tasks in robotic applications. Nevertheless, in the original formulation the SAP descriptor is not invariant against rotations around the camera axis. This paper explains and evaluates two methods which pre-process the input data to yield repeatably well-aligned point clouds for the cimputation of the SAP descriptor. Whe show that the SAP descriptor can be rendered robust against rotations while retaining almost the full performance of the original approach which is superior to GFPFH, GRSD and VFH.