A HIERARCHICAL 3D CIRCLE DETECTION ALGORITHM APPLIED IN A GRASPING SCENARIO

Emre Baseski, Dirk Kraft, Norbert Kruger

Abstract

In this work, we address the problem of 3D circle detection in a hierarchical representation which contains 2D and 3D information in the form of multi-modal primitives and their perceptual organizations in terms of contours. Semantic reasoning on higher levels leads to hypotheses that then become verified on lower levels by feedback mechanisms. The effects of uncertainties in visually extracted 3D information can be minimized by detecting a shape in 2D and calculating its dimensions and location in 3D. Therefore, we use the fact that the perspective projection of a circle on the image plane is an ellipse and we create 3D circle hypotheses from 2D ellipses and the planes that they lie on. Afterwards, these hypotheses are verified in 2D, where the orientation and location information is more reliable than in 3D. For evaluation purposes, the algorithm is applied in a robotics application for grasping cylindrical objects.

References

  1. Chernov, N. and Lesort, C. (2005). Least Squares Fitting of Circles. J. Math. Imaging Vis., 23(3):239-252.
  2. Duda, R. O., Hart, P. E., and Stork, D. G. (2000). Pattern Classification. Wiley-Interscience Publication.
  3. Ji, Q. and Haralick, R. M. (1999). A Statistically Efficient Method for Ellipse Detection. In ICIP (2), pages 730- 734.
  4. Jiang, X. and Cheng, D.-C. (2005). Fitting of 3D Circles and Ellipses Using a Parameter Decomposition Approach. In 3DIM 7805: Proceedings of the Fifth International Conference on 3-D Digital Imaging and Modeling, pages 103-109. IEEE Computer Society.
  5. Lowe, D. G. (1987). Three-Dimensional Object Recognition from Single Two-Dimensional Images. Artificial Intelligence, 31(3):355-395.
  6. Pilu, M., Fitzgibbon, A., and Fisher, R. (1996). EllipseSpecific Direct Least-Square Fitting. In In Proc. IEEE ICIP.
  7. Pugeault, N., Kalkan, S., Bas¸eski, E., Wörgötter, F., and Krüger, N. (2008). Reconstruction Uncertainty and 3D Relations. In Proceedings of Int. Conf. on Computer Vision Theory and Applications (VISAPP'08).
  8. Xavier, J., Pacheco, M., Castro, D., Ruano, A., and Nunes, U. (2005). Fast Line, Arc/Circle and Leg Detection from Laser Scan Data in a Player Driver. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 3930- 3935.
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Paper Citation


in Harvard Style

Baseski E., Kraft D. and Kruger N. (2009). A HIERARCHICAL 3D CIRCLE DETECTION ALGORITHM APPLIED IN A GRASPING SCENARIO . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 496-502. DOI: 10.5220/0001796004960502


in Bibtex Style

@conference{visapp09,
author={Emre Baseski and Dirk Kraft and Norbert Kruger},
title={A HIERARCHICAL 3D CIRCLE DETECTION ALGORITHM APPLIED IN A GRASPING SCENARIO},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={496-502},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001796004960502},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - A HIERARCHICAL 3D CIRCLE DETECTION ALGORITHM APPLIED IN A GRASPING SCENARIO
SN - 978-989-8111-69-2
AU - Baseski E.
AU - Kraft D.
AU - Kruger N.
PY - 2009
SP - 496
EP - 502
DO - 10.5220/0001796004960502