| R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Proceedings of International Conference on Computer Vision (ICCV '98), pages 863--869, 1998. |
....consequence, the control of the rotation of the camera can be decoupled from the control of the translation. This important fact characterizes the new class of model free visual servoing methods analyzed in this paper. The translation of the camera can be controlled directly, as it was proposed in [1] (using thus a model free position based approach) or using an hybrid approach as we proposed in [16] it consists in combining visual features obtained directly from the image with features expressed in the Euclidean space) Another interesting property of the model free approaches is that it is ....
....of calibration errors in the hand eye transformation. Global asymptotic stability is important since it guarantees that the system will converge even if the initial error is very large. Recently, Taylor et al. 22] proposed a position based approach, very similar to the one proposed by Basri [1], finding local stability conditions resembling to those proposed in [15] As it will be shown in this paper, this is not surprising, since model free position based approaches are particular cases of the class we analyze in this paper. We will show that the calibration error that can be tolerated ....
[Article contains additional citation context not shown here]
R. Basri, E. Rivlin, and I. Shimshoni, "Visual homing: Surfing on the epipoles," in IEEE Int. Conf. on Computer Vision, pp. 863--869, Bombay, India, January 1998.
.... the essential matrix representing SFM becomes the fundamental matrix representing the epipolar geometry of an image pair [49] It is determined from at least eight points, and linear estimation is feasible and e#cient [31] Basic visual homing based on epipoles is actually proposed in [1]. Above that, the fundamental matrix allows for three dimensional reconstruction of scene structure. In the uncalibrated case, 22] 30] it allows to recover structure and camera motion up to a fixed but unknown projective transformation of the ambient space. Approaches to visual servoing which ....
....at equation (3.1) T T and by similarity also H T have the characteristic polynomial (1 #) 0 and hence a quadruple eigenvalue # = 1. Since rank(T T I) 1andrank(T T I) 0, their common Jordan matrix [41] has one Jordan block of order two, J 2 = and two of order one, J 1 =[ 1 ]. Among the possible permutations of blocks, the one having the form of a rigid displacement is chosen as Jordan matrix. q.e.d. 3.4) Looking at equation (3.3) and rescaling by 1 # shows the matrix SET = diag ( 1)TZ H PE . 3.8) to be a possible decomposition of H T , which can be ....
[Article contains additional citation context not shown here]
R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Proceedings of the International Conference on Computer Vision, (ICCV'98), pages 863--869, Bombay, India, January 1998.
....order to obtain high precision. T ypically, 400 edge measurements are made per image frame. The use of visual feedback ouput bysuchtracking systems for robotic control is increasingly becoming an attractive proposition. A distinction is often made [7] bet w eenimage base d [8] and position base d [9] visual servoing. The approach presented here projects the action of three dimensional motion into the image where it is fitted to image measurements. 2 Theoretical framework The approach proposed here for tracking a known 3 dimensional structure is based upon maintaining an estimate of the ....
R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Pr oceedings of International Conference on Computer Vision (ICCV '98), pages 863--869, 1998.
....the appropriate Jacobian. The method has problems with discontinuous functions, and has no allowance for orientation of the gripper. A paraperspective model has been used for the visual component of the robot controller in [6] This requires calibration for the focal length and full equations. In [7] motion is based on a target image which contains components of the present view. The image then moves to match the target to the actual image. They conclude that perspective models are not required for head based cameras (long distance compared to focal length) It can also handle moving objects ....
Basri R et al., "Visual homing: surfing on the epipoles", Int Jnl of Computer Vision, 1999, pp117-137.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. International Journal of Computer Vision, 33(2), 1999. To appear.
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R. Basri, E. Rivlin, and I. Shimshoni, #Visual homing: surfing on the epipoles,# 6th Int. Conf. Computer Vision (ICCV-98), Bombay: pp. 863#869, 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Proceedings of International Conference on Computer Vision (ICCV '98), pages 863--869, 1998.
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Basri, R., Rivlin, E., Shimshoni, I.: Visual homing: Surfing on the epipoles. Technical Report MCS99-10, Weizmann Institute of Science, Mathematics & Computer Science (1999)
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R. Basri, E. Rivlin, and I. Shimshoni. "Visual homing: Surfing on the epipoles.". In International Conference on Computer Vision, pages 863--869, 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In IEEE Conference on Computer Vision, pages 863--869, 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. "Visual homing: Surfing on the epipoles.". In International Conference on Computer Vision, pages 863-- 869, 1998.
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Basri, R., Rivlin, E., and Shimshoni, I. 1998. Visual homing: Surfing on the epipoles. In the Proceedings of the Sixth International Conference on Computer Vision (ICCV-98), Bombay, India, pp.
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Basri, R., Rivlin, E., and Shimshoni, I. (1998). Visual homing: Surfing on the epipoles. In IEEE Int. Conf. on Computer Vision, pages 863--869, Bombay, India.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In IEEE Int. Conf. on Computer Vision, pages 863--869, Bombay, India, January 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. IEEE Int. Conf. on Computer Vision, pp. 863--869, Bombay, India, January 1998.
No context found.
R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In IEEE Int. Conf. on Computer Vision, pages 863--869, Bombay, India, January 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: surfing on the epipole. International Journal of Computer Vision, 33(2):22--39, 1999.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: surfing on the epipole. International Journal of Computer Vision, 33(2):22--39, 1999.
No context found.
R. Basri, E. Rivlin, and I. Shimshoni, "Visual homing: Surfing on the epipoles," in IEEE Int. Conf. on Computer Vision, pp. 863--869, Bombay, India, January 1998.
No context found.
R. Basri, E. Rivlin, and I. Shimshoni, "Visual homing: Surfing on the epipoles," in IEEE Int. Conf. on Computer Vision, pp. 863--869, Bombay, India, January 1998.
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R. Basri, E. Rivlin, and I. Shimshoni, "Visual homing: Surfing on the epipoles." in ICCV, 1998, pp. 863--869.
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R. Basri, E. Rivlin, and I. Shimshoni, "Visual homing: Surfing on the epipoles." in ICCV, 1998, pp. 863--869.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In ICCV98, pages 863--869, 1998.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. Int. Journal of Computer Vision (IJCV), 33(2):1--21, September 1999.
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R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Proc. Int. Conference on Computer Vision (ICCV), pages 863--869, 1998.
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