Object class and instance recognition on rgb-d data

Viktor Seib; Susanne Christ-Friedmann; Susanne Thierfelder; Dietrich Paulus

doi:10.1117/12.2049915

24 December 2013 Object class and instance recognition on rgb-d data

Viktor Seib, Susanne Christ-Friedmann, Susanne Thierfelder, Dietrich Paulus

Proceedings Volume 9067, Sixth International Conference on Machine Vision (ICMV 2013); 90670J (2013) https://doi.org/10.1117/12.2049915
Event: Sixth International Conference on Machine Vision (ICMV 13), 2013, London, United Kingdom

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.

Citation Download Citation

Viktor Seib, Susanne Christ-Friedmann, Susanne Thierfelder, and Dietrich Paulus "Object class and instance recognition on rgb-d data", Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90670J (24 December 2013); https://doi.org/10.1117/12.2049915

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