Probabilistic curve evolution using particle filters

Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference, CDC-ECC '05

Volumn 2005, Issue , 2005, Pages 6335-6340

  Pan, Yongsheng ^a   Birdwell, J Douglas ^a   Djouadi, Seddik M ^a  

^a UNIVERSITY OF TENNESSEE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIGITAL FILTERS; NONLINEAR SYSTEMS; SET THEORY; STATE ESTIMATION; TOPOLOGY;

BAYESIAN FRAMEWORK; CONTOUR MODEL; CURVE EVOLUTION; PARTICLE FILTERS;

PROBABILISTIC LOGICS;

EID: 33847182736     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2005.1583177     Document Type: Conference Paper

References (15)

1. S. Kichenassamy, A. Kumar, P. Olver, A. Tannenbaum, and A. Yezzi, "Gradient flows and geometric active contour models," Fifth Int. Conf. Computer Vision, pp. 810-815, 1995.
2. L. Vese and T. Chan, "A multiphase level set framework for image segmentation using the Mumford and Shah model," Int. J. Comput. Vis., V. 50, no. 3, pp. 271-293, 2002.
3. A. Tsai, A. Yezzi, and A. Willsky, "Curve evolution implementation of the Mumford-Shah functional for image segmentation denoising, interpolation, and magnification," IEEE Trans. Image Processing, V. 10, no. 8, pp. 1169-1186, Aug. 2001.
4. N. Paragios, and R. Deriche, "Coupled geodesic active regions for image segmentation: a level set approach," Proceedings ECCV, Dublin, V. II, pp. 224-240.
5. G. Unal, H. Krim, and A. Yezzi, "Stochastic differential equations and geometric flows," IEEE Trans. Image Processing, vol. 11, no. 12, pp. 1405 - 1416, Dec. 2002.
6. O. Juan, R. Keriven, G. Postelnucu, "Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours," Research Report 04-01, May 2004.
7. D. Terzopoulos, R. Szeliski, "Tracking with Kalman snakes," pp. 3-20, in Active Vision, A. Blake and A. Yuille (eds), MIT Press, 1992.
8. N. Peterfreund, "Robust tracking of position and velocity with Kalman snakes," IEEE Trans. PAMI, V. 21, no. 6, pp. 564-569, June 1999.
9. M. Sanjeev Arulampalam, S. Maskell, N. Gordon, T. Clapp, "A tutorial on particle filters for on-line nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Processing, V. 50, no. 2, pp. 174-188, Feb. 2002.
10. P.M. Djuric, etc, "Particle filtering", IEEE Signal Processing Magazine, V. 20, no. 5, pp. 19-38, Sep. 2003.
11. J.A.Sethian, Level Set Methods and Fast Matching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision and Materials Science, Cambridge University Press, 2000.
12. Y. Pan, J.D. Birdwell, S. Djouadi, "A new gradient and region based geometric snake," Proceedingss of ICASSP 2005, Philadelphia, PA, USA, pp. II-745 -II-748, Mar. 18-23, 2005.
13. P. Perona, J. Malik, "Scale-space and edge detection using anisotropic diffusion," IEEE Trans. PAMI, V. 12, no. 7, pp. 629-639, July 1990.
14. L. Alvarez, R. Lions, J. Morel, "Image Selective Smoothing and Edge Detection by Nonlinear Diffusion II," SIAM J. Numer. Anal. V. 29, no. 3, pp. 845-866, June 1992.
15. Olle Haggstrom, "Finite Markov Chains and Algorithmic Applications", Cambridge University Press, 2002.