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Conference Papers Year : 2004

Robust model-based tracking for robot vision

Abstract

This paper proposes a real-time, robust and efficient 3D model-based tracking algorithm for visual servoing. A virtual visual servoing approach is used for monocular 3D tracking. This method is similar to more classical non-linear pose computation techniques. A concise method for derivation of efficient distance-to-contour interaction matrices is described. An oriented edge detector is used in order to provide real-time tracking of points normal to the object contours. Robustness is obtained by integrating a M-estimator into the virtual visual control law via an iteratively re-weighted least squares implementation. The method presented in this paper has been validated on several 2D 1/2 visual servoing experiments considering various objects. Results show the method to be robust to occlusion, changes in illumination and miss-tracking.
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Dates and versions

inria-00352025 , version 1 (12-01-2009)

Identifiers

  • HAL Id : inria-00352025 , version 1

Cite

Andrew Comport, E. Marchand, François Chaumette. Robust model-based tracking for robot vision. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'04, 2004, Sendai, Japan. pp.692--697. ⟨inria-00352025⟩
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