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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
© 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Erstellt am: 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
S.409-416
International Conference on Humanoid Robots (Humanoids) <12, 2012, Osaka>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IPA ()
surface; approximation; Datenmanagement; object classification; machine vision; maschinelles Sehen; Oberfläche; Objekterkennung; Roboter; Kamera

Abstract
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.

: http://publica.fraunhofer.de/dokumente/N-225289.html