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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.
Type de document :
Communication dans un congrès
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'04, 2004, Sendai, Japan. 1, pp.692--697, 2004
https://hal.inria.fr/inria-00352025
Contributeur : Eric Marchand
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Soumis le : lundi 12 janvier 2009 - 13:53:12
Dernière modification le : vendredi 16 novembre 2018 - 01:39:55
Document(s) archivé(s) le : mardi 8 juin 2010 - 19:31:35
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. 1, pp.692--697, 2004. 〈inria-00352025〉
