Integration of fuzzy spatial information in tracking based on particle filtering

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 41, Issue 3, 2011, Pages 635-649

  Widynski, Nicolas ^a   Dubuisson, Séverine ^b   Bloch, Isabelle ^c  

^a CNRS   (France)

^b SORBONNE UNIVERSITÉ   (France)

^c INSTITUT TELECOM   (France)

Author keywords

fuzzy spatial information; Fuzzy shape tracking; particle filter

Indexed keywords

FILTERING TECHNIQUE; FUZZY FRAMEWORKS; FUZZY MODELING; FUZZY MODELS; FUZZY-SHAPE TRACKING; NOVEL METHODS; ON DYNAMICS; PARTICLE FILTER; PARTICLE FILTERING; PRIOR INFORMATION; REAL VIDEO SEQUENCES; SHAPE INFORMATION; SPATIAL INFORMATIONS; SPATIAL RELATIONS; SYNTHETIC DATA; TRACKED OBJECTS; TRACKING PROBLEM;

DISTRIBUTED COMPUTER SYSTEMS; NONLINEAR FILTERING; SEMANTICS; TARGET TRACKING;

FUZZY FILTERS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FUZZY LOGIC; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FUZZY LOGIC; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED;

EID: 79957449372     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2010.2064767     Document Type: Article

References (28)

1. E. Arnaud and E. Mémin, "Partial linear Gaussian models for tracking in image sequences using Sequential Monte Carlo methods," Int. J. Comput. Vis., vol. 74, no. 1, pp. 75-102, Aug. 2007. (Pubitemid 46673105)
2. S. Arulampalam, S. Maskell, and N. Gordon, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002. (Pubitemid 34291500)
3. S.M. Arulampalam, B. Ristic, N. Gordon, and T. Mansell, "Bearings-only tracking of manoeuvring targets using particle filters," EURASIP J. Appl. Signal Process., vol. 2004, pp. 2351-2365, Jan. 2004. (Pubitemid 40088507)
4. I. Bloch, "Information combination operators for data fusion: A comparative review with classification," IEEE Trans. Syst., Man, Cybern., vol. 26, no. 1, pp. 52-67, Jan. 1996. (Pubitemid 126784519)
5. I. Bloch, "Fuzzy spatial relationships for image processing and interpretation: A review," Image Vis. Comput., vol. 23, no. 2, pp. 89-110, Feb. 2005.
6. I. Bloch, O. Colliot, and R. Cesar, "On the ternary spatial relation between," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 36, no. 2, pp. 312-327, Apr. 2006.
7. W. Y. Chang, C. S. Chen, and Y. D. Jian, "Visual tracking in highdimensional state space by appearance-guided particle filtering," IEEE Trans. Image Process., vol. 17, no. 7, p. 14, Jul. 2008.
8. Z. Chen, "Bayesian filtering: From Kalman filters to particle filters, and beyond," Tech. Rep., McMaster Univ., Hamilton, ON, Canada, 2003.
9. A. Doucet and A. M. Johansen, "A tutorial on particle filtering and smoothing: Fifteen years later," Tech. Rep., Dept. Statistics, Univ. British Columbia, Vancouver, BC, Canada, 2008.
10. A. Doucet, S. Godsill, and C. Andrieu, "On sequential Monte Carlo sampling methods for Bayesian filtering," Statist. Comput., vol. 10, no. 3, pp. 197-208, Jul. 2000.
11. A. Doucet, N. De Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice. New York: Springer-Verlag, 2001.
12. D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications. New York: Academic, 1980.
13. N. J. Gordon, D. J. Salmond, and A. F. Smith, "Novel approach to nonlinear/non-Gaussian Bayesian state estimation," Proc. Inst. Elect. Eng.-F, Radar Signal Process., vol. 140, no. 2, pp. 107-113, Apr. 1993.
14. M. Isard and A. Blake, "CONDENSATION-Conditional density propagation for visual tracking," Int. J. Comput. Vis., vol. 29, no. 1, pp. 5-28, Aug. 1998. (Pubitemid 128523364)
15. M. Isard and A. Blake, "A mixed-state condensation tracker with automatic model-switching," in Proc. 6th Int. Conf. Comput. Vis., 1998, pp. 94-101.
16. R. E. Kalman, "A new approach to linear filtering and prediction problems," Trans. ASME, J. Basic Eng., vol. 82, pp. 35-45, 1960.
17. R. Karlsson and N. Bergman, "Auxiliary particle filters for tracking a maneuvering target," in Proc. 39th IEEE Conf. Decision Control, 2000, vol. 4, pp. 3891-3895. (Pubitemid 32528272)
18. J. S. Liu, "Metropolized independent sampling with comparisons to rejection sampling and importance sampling," Statist. Comput., vol. 6, no. 2, pp. 113-119, Jun. 1996. (Pubitemid 126724248)
19. S. McGinnity and G. W. Irwin, "Multiple model bootstrap filter for maneuvering target tracking," IEEE Trans. Aerosp. Electron. Syst., vol. 36, no. 3, pp. 1006-1012, Jul. 2000.
20. K. Okuma, A. Taleghani, O. De Freitas, J. J. Little, and D. G. Lowe, "A boosted particle filter: Multitarget detection and tracking," in Proc. ECCV, 2004, pp. 28-39.
21. V. Pavlovic, J. M. Rehg, and J. Maccormick, "Learning switching linear models of human motion," in Proc. Neural Inf. Process. Syst., 2000, pp. 981-987.
22. P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, "Color-based probabilistic tracking," in Proc. 7th Eur. Conf. Comput. Vis.-Part I, 2002, pp. 661-675.
23. M. Pitt and N. Shephard, "Filtering via simulation: Auxiliary particle filters," J. Amer. Statist. Assoc., vol. 94, no. 446, pp. 590-599, Jun. 1999.
24. Y. Rathi, N. Vaswani, and A. Tannenbaum, "A generic framework for tracking using particle filter with dynamic shape prior," IEEE Trans. Image Process., vol. 16, no. 5, pp. 1370-1382, May 2007. (Pubitemid 46629562)
25. B. L. Welch, "The generalization of 'Student's' problem when several different population variances are involved," Biometrika, vol. 34, no. 1/2, pp. 28-35, 1947.
26. A. Yilmaz, O. Javed, and M. Shah, "Object tracking: A survey," ACM Comput. Surv., vol. 38, no. 4, 2006, article 13.
27. L. A. Zadeh, "The concept of a linguistic variable and its application to approximate reasoning," Inf. Sci., vol. 8, no. 3, pp. 199-249, 1975.
28. L. A. Zadeh, "Probability measures of fuzzy events," J. Math. Anal. Appl., vol. 23, no. 2, pp. 421-427, 1968.