Structure from Motion Using Sequential Monte Carlo Methods
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[1] Jun S. Liu,et al. Sequential Monte Carlo methods for dynamic systems , 1997 .
[2] Andrew Blake,et al. A Probabilistic Exclusion Principle for Tracking Multiple Objects , 2000, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[3] Alex Pentland,et al. Recursive Estimation of Motion, Structure, and Focal Length , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[4] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[5] Rama Chellappa,et al. Statistical Analysis of Inherent Ambiguities in Recovering 3-D Motion from a Noisy Flow Field , 1992, IEEE Trans. Pattern Anal. Mach. Intell..
[6] John Oliensis,et al. A Critique of Structure-from-Motion Algorithms , 2000, Comput. Vis. Image Underst..
[7] G. Kitagawa. Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models , 1996 .
[8] S. P. Mudur,et al. Three-dimensional computer vision: a geometric viewpoint , 1993 .
[9] H. C. Longuet-Higgins,et al. A computer algorithm for reconstructing a scene from two projections , 1981, Nature.
[10] Carlo Tomasi,et al. Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[11] Rama Chellappa,et al. Reduction of inherent ambiguities in structure from motion problem using inertial data , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).