Model-free optimal trajectories in the image space: application to robot vision control, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001. ,
DOI : 10.1109/CVPR.2001.990661
URL : https://hal.archives-ouvertes.fr/inria-00352137
Structure and Motion for Dynamic Scenes ??? The Case of Points Moving in Planes, IEEE Eur. Conf. on Computer Vision, pp.867-882, 2002. ,
DOI : 10.1007/3-540-47967-8_58
URL : https://hal.archives-ouvertes.fr/inria-00525652
Particle-Imaging Techniques for Experimental Fluid Mechanics, Annual Review of Fluid Mechanics, vol.23, issue.1, pp.261-304, 1991. ,
DOI : 10.1146/annurev.fl.23.010191.001401
Experimental results from a comparative study on correlation-type registration algorithms, Robust Computer Vision, pp.268-289, 1992. ,
Determining optical flow, Artificial Intelligence, vol.17, issue.1-3, pp.185-203, 1981. ,
DOI : 10.1016/0004-3702(81)90024-2
Good features to track, IEEE Int. Conf. on Computer Vision and Pattern Recognition, pp.593-600, 1994. ,
Real-time feature tracking and outlier rejection with changes in illumination, IEEE Int. Conf. on Computer Vision, pp.684-689, 2001. ,
Making good features track better, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), pp.178-183, 1998. ,
DOI : 10.1109/CVPR.1998.698606
Occlusion robust adaptative template tracking, IEEE Int. Conf. on Computer Vision, pp.678-683, 2001. ,
Visual tracking of a moving target by a camera mounted on a robot: a combination of control and vision, IEEE Transactions on Robotics and Automation, vol.9, issue.1, pp.14-35, 1993. ,
DOI : 10.1109/70.210792
Active Contours, 1998. ,
DOI : 10.1007/978-1-4471-1555-7
A New Approach to Linear Filtering and Prediction Problems, Transactions of the ASME -Journal of Basic Engineering, pp.35-45, 1960. ,
DOI : 10.1115/1.3662552
Bayesian analysis of times series and dynamic models, j. c. spall ed., Marcel Dekker inc., ch. recursive estimation for nonlinear dynamic systems, 1988. ,
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, IEEE Transactions on Signal Processing, vol.50, issue.2, pp.174-188, 2002. ,
DOI : 10.1109/78.978374
On sequential Monte Carlo sampling methods for Bayesian filtering, Statistics and Computing, vol.10, issue.3, pp.197-208, 2000. ,
DOI : 10.1023/A:1008935410038
Stochastic Tracking of 3D Human Figures Using 2D Image Motion, IEEE Eur. Conf. on Computer Vision, pp.702-718, 2000. ,
DOI : 10.1007/3-540-45053-X_45
Color-Based Probabilistic Tracking, IEEE Eur. Conf. on Computer Vision, pp.661-675, 2002. ,
DOI : 10.1007/3-540-47969-4_44
Condensation ? conditional density propagation for visual tracking, International Journal of Computer Vision, vol.29, issue.1, pp.5-28, 1998. ,
DOI : 10.1023/A:1008078328650
BraMBLe: a Bayesian multiple-blob tracker, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.34-41, 2001. ,
DOI : 10.1109/ICCV.2001.937594
A mixed-state condensation traker with automatic model-switching, IEEE Int. Conf. on Computer Vision, pp.107-112, 1998. ,
Implicit pobabilistic models of human motion for synthesis and tracking, IEEE Eur. Conf. on Computer Vision, pp.784-800, 2002. ,
Space-Time Tracking, IEEE Eur. Conf. on Computer Vision, pp.801-812, 2001. ,
DOI : 10.1007/3-540-47969-4_53
Sequential Imputations and Bayesian Missing Data Problems, Journal of the American Statistical Association, vol.52, issue.425, pp.278-288, 1994. ,
DOI : 10.1080/01621459.1987.10478458
Novel approach to nonlinear/non-Gaussian Bayesian state estimation, IEEE Processing-F (Radar and Signal Processing, pp.107-113, 1993. ,
DOI : 10.1049/ip-f-2.1993.0015
Sequential Monte Carlo Methods for Dynamic Systems, Journal of the American Statistical Association, vol.24, issue.443, pp.1032-1044, 1998. ,
DOI : 10.1073/pnas.94.26.14220
Highest density gates for target tracking, IEEE Transactions on Aerospace and Electronic Systems, vol.36, issue.1, pp.47-55, 2000. ,
DOI : 10.1109/7.826311
Guiding random particles by deterministic search, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.323-330, 2001. ,
DOI : 10.1109/ICCV.2001.937536
A probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions, IEEE Eur. Conf. on Computer Vision, pp.909-924, 1998. ,
DOI : 10.1007/BFb0055712
The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields, Computer Vision and Image Understanding, vol.63, issue.1, pp.75-104, 1996. ,
DOI : 10.1006/cviu.1996.0006
Robust Multiresolution Estimation of Parametric Motion Models, Journal of Visual Communication and Image Representation, vol.6, issue.4, pp.348-365, 1995. ,
DOI : 10.1006/jvci.1995.1029
Measuring visual motion from image sequences, 1987. ,
Kalman filter-based algorithms for estimating depth from image sequences, International Journal of Computer Vision, vol.8, issue.3, pp.209-238, 1989. ,
DOI : 10.1007/BF00133032
Image-flow computation: An estimation-theoretic framework and a unified perspective, Computer Vision, Graphics, and Image Processing : Image Understanding, pp.152-177, 1992. ,
DOI : 10.1016/1049-9660(92)90037-4
Estimating uncertainty in SSD-based feature tracking, Image and Vision Computing, vol.20, issue.1, pp.47-58, 2002. ,
DOI : 10.1016/S0262-8856(01)00076-2
Computing occluding and transparent motions, International Journal of Computer Vision, vol.1, issue.1, pp.5-16, 1994. ,
DOI : 10.1007/BF01420982
MRF-based motion segmentation exploiting a 2D motion model robust estimation, Proceedings., International Conference on Image Processing, pp.628-632, 1995. ,
DOI : 10.1109/ICIP.1995.537713
Performance of digital image velocimetry processing techniques, Experiments in fluids, pp.106-115, 2002. ,
DOI : 10.1007/s003480200011