The KIT object models database: An object model database for object recognition, localization and manipulation in service robotics

@article{Kasper2012TheKO,
  title={The KIT object models database: An object model database for object recognition, localization and manipulation in service robotics},
  author={Alexander Kasper and Zhixing Xue and R{\"u}diger Dillmann},
  journal={I. J. Robotics Res.},
  year={2012},
  volume={31},
  pages={927-934}
}
For the execution of object recognition, localization and manipulation tasks, most algorithms use object models. Most models are derived from, or consist of two-dimensional (2D) images and/or three-dimensional (3D) geometric data. The system described in this article was constructed specifically for the generation of such model data. It allows 2D image and 3D geometric data of everyday objects be obtained semi-automatically. The calibration provided allows 2D data to be related to 3D data… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 12 REFERENCES

A large-scale hierarchical multi-view RGB-D object dataset

  • 2011 IEEE International Conference on Robotics and Automation
  • 2011
VIEW 1 EXCERPT

Integrating Vision Toolkit. http://ivt.source forge.net

P Azad
  • 2010
VIEW 2 EXCERPTS

Stanford spherical gantry. http://graphics. stanford.edu/projects/gantry

M Levoy
  • 2010
VIEW 1 EXCERPT

The Columbia grasp database

  • 2009 IEEE International Conference on Robotics and Automation
  • 2009
VIEW 1 EXCERPT

Computer vision: Principles and practice. Brentford: Elektor

P Azad, T Gockel, R Dillmann
  • 2008
VIEW 1 EXCERPT

The Princeton Shape Benchmark

  • Proceedings Shape Modeling Applications, 2004.
  • 2004
VIEW 1 EXCERPT