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Proceedings Paper

Object class and instance recognition on rgb-d data
Author(s): Viktor Seib; Susanne Christ-Friedmann; Susanne Thierfelder; Dietrich Paulus
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Paper Abstract

We present a novel approach for combining 3D depth and visual information for object class and object instance recognition. Object classes are recognized by first assigning local geometric primitive labels using a CRF, followed by an SVM classification. Object instances are recognized using Hough-transform clustering of SURF features. Both algorithms perform well on publicly available object databases as well as on acquired data with an RGB-D camera. The ob - ject instance recognition algorithm was further evaluated during the RoboCup world championship 2012 in Mexico-City and won the first place in the Technical Challenge of the @Home-league.

Paper Details

Date Published: 24 December 2013
PDF: 7 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90670J (24 December 2013); doi: 10.1117/12.2049915
Show Author Affiliations
Viktor Seib, Univ. Koblenz-Landau (Germany)
Susanne Christ-Friedmann, Univ. Koblenz-Landau (Germany)
Susanne Thierfelder, Univ. Koblenz-Landau (Germany)
Dietrich Paulus, Univ. Koblenz-Landau (Germany)

Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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