Embedding motion in model-based stochastic tracking

IEEE Transactions on Image Processing

Volumn 15, Issue 11, 2006, Pages 3514-3530

  Odobez, Jean Marc ^a,b   Gatica Perez, Daniel ^a,b   Ba, Sileye O ^a,b  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

^b EPFL   (Switzerland)

Author keywords

Monte Carlo methods; Motion features; Sequential estimation; Visual tracking

Indexed keywords

MONTE CARLO METHODS; MOTION ESTIMATION; RANDOM PROCESSES; STATE SPACE METHODS; TRACKING (POSITION); TRAJECTORIES;

EMBEDDING MOTION; MOTION FEATURES; SEQUENTIAL ESTIMATION; STOCHASTIC TRACKING; VISUAL TRACKING;

OBJECT RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; METHODOLOGY; MOTION; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; MOTION; PATTERN RECOGNITION, AUTOMATED; STOCHASTIC PROCESSES;

EID: 33750339658     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2006.877497     Document Type: Article

References (38)

1. J.-M. Odobez and D. Gatica-Perez, "Embedding motion in model-based stochastic tracking," in Proc. 17th Int. Conf. Pattern Recognition, Cambridge, U.K., Aug. 2004, pp. II:815-818.
2. A. Blake and M. Isard, Active Contours. Berlin, Germany: Springer-Verlag, 1998.
3. S. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking," IEEE Trans. Signal Process., vol. 50, no. 2, pp. 174-188, Feb. 2002.
4. A. Doucet, N. de Freitas, and N. Gordon, Sequential Monte Carlo Methods in Practice. Berlin, Germany: Springer-Verlag, 2001.
5. D. Comaniciu, V. Ramesh, and P. Meer, "Real-time tracking of nonrigid objects using mean shift," in Proc. IEEE Conf. Computer Vision Pattern Recognition, 2000, pp. II:142-149.
6. Y. Wu and T. Huang, "A co-inference approach for robust visual tracking," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. II:26-33.
7. Y. Raja, S. McKenna, and S. Gong, "Colour model selection and adaptation in dynamic scenes," in Proc. 5th Eur. Conf. Computer Vision, 1998, vol. 1406, LNCS, pp. 460-474.
8. P. Pérez, C. Hue, J. Vermaak, and M. Gangnet, "Color-based probabilistic tracking," in Proc. 7th Eur. Conf. Computer Vision, Copenhagen, Denmark, Jun. 2002, vol. 2350, LNCS, pp. 661-675.
9. E. Arnaud, E. Mémin, and B. C. Frias, "Filtrage conditionnel pour la trajectographie dans des séquences d'images - Application au suivi de points," presented at the 14th Conf. Reconnaissance des Formes et Intelligence Artificielle Toulouse, France, Jan. 2004.
10. M. J. Black and A. D. Jepson, "A probabilistic framework for matching temporal trajectories: Condensation-based recognition of gestures and expressions," in Proc. 5th Eur. Conf. Computer Vision, Freiburg, Germany, 1998, vol. 1406, LNCS, pp. 909-924.
11. M. Isard and A. Blake, "ICONDENSATION: Unifying low-level and high-level tracking in a stochastic framework," in Proc. 5th Eur. Conf. Computer Vision, 1998, vol. 1406, LNCS, pp. 893-908.
12. Y. Rui and Y. Chen, "Better proposal distribution: Object tracking using unscented particle filter," in Proc. IEEE Conf. Computer Vision Pattern Recognition, Dec. 2001, pp. II:786-793.
13. K. Toyama and A. Blake, "Probabilistic tracking in a metric space," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. II:50-57.
14. 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, 2000.
15. J. Sullivan and J. Rittscher, "Guiding random particles by deterministic search," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. I:323-330.
16. H. Tao, H. Sawhney, and R. Kumar, "Object tracking with Bayesian estimation of dynamic layer representations," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 1, pp. 75-89, Jan. 2001.
17. A. Jepson, D. J. Fleet, and T. F. El-Maraghi, "Robust on-line appearance models for visual tracking," IEEE Trans. Pattern Anal. Mach. Intell., vol. 25, no. 10, pp. 661-673, Oct. 2003.
18. H. T. Nguyen, M. Worring, and R. van den Boomgaard, "Occlusion robust adaptive template tracking," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. I:678-683.
19. M. Black and A. Jepson, "Eigentracking: Robust matching and tracking of articulated objects using a view based representation," Int. J. Comput. Vis., vol. 26, no. 1, pp. 63-84, 1998.
20. A. Rahimi, L. Morency, and T. Darrell, "Reducing drift in parametric motion tracking," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. I:315-322.
21. J. Vermaak, P. Pérez, M. Gangnet, and A. Blake, "Towards improved observation models for visual tracking: Selective adaptation," in Proc. 7th Eur. Conf. Computer Vision, Copenhagen, Denmark, 2002, vol. 2350, LNCS, pp. 645-660.
22. H. Sidenbladh and M. Black, "Learning image statistics for Bayesian tracking," in Proc. 8th IEEE Int. Conf. Computer Vision, Vancouver, BC, Canada, Jul. 2001, pp. II:709-716.
23. H. Sidenbladh, M. Black, and D. Fleet, "Stochastic tracking of 3d human figures using 2d image motion," in Proc. 6th Eur. Conf. Computer Vision, Dublin, Ireland, Jun. 2000, vol. 1843, LNCS, pp. II:702-718.
24. P. Pérez, J. Vermaak, and A. Blake, "Data fusion for visual tracking with particles," Proc. IEEE, vol. 92, no. 3, pp. 495-513, Mar. 2004.
25. D. Gatica-Perez, G. Lathoud, I. McCowan, and J.-M. Odobez, "A mixed-state I-particle filter for multi-camera speaker tracking," presented at the IEEE Int. Conf. Computer Vision Workshop on Multimedia Technologies for E-Learning and Collaboration 2003.
26. M. K. Pitt and N. Shephard, "Filtering via simulation: Auxiliary particle filters," J. Amer. Statist. Assoc., vol. 94, no. 446, pp. 590-599, 1999.
27. E. Arnaud and E. Mémin, "Optimal importance sampling for tracking in image sequences:APplication to point tracking," in Proc. 8th Eur. Conf. Computer Vision, Prague, Czech Republic, May 2004, vol. 3023, LNCS, pp. III:302-314.
28. U. Grenander, Y. Chow, and D. Keenan, HANDS. A Pattern Theoretical Study of Biological Shapes. New-York: Springer-Verlag, 1991.
29. A. Tekalp, Digital Video Processing. Upper Saddle River, NJ: Prentice-Hall, 1995, Signal Processing Series.
30. J. Sullivan, A. Blake, M. Isard, and J. MacCormick, "Object localization by Bayesian correlation," in Proc. 7th IEEE Int. Conf. Computer Vision, 1999, pp. II:1068-1075.
31. J. Sullivan, A. Blake, and J. Rittscher, "Statistical foreground modeling for object localisation," in Proc. 6th Eur. Conf. Computer Vision, 2000, vol. 1843, LNCS, pp. II:307-323.
32. Y. Chen and Y. Rui, "Real-time speaker tracking using particle filter sensor fusion," Proc. IEEE, vol. 92, no. 3, pp. 485-494, Mar. 2004.
33. J.-M. Odobez and P. Bouthemy, "Robust multiresolution estimation of parametric motion models," J. Vis. Commun. Image Repres., vol. 6, no. 4, pp. 348-365, Dec. 1995.
34. P. Hubert, Robust Statistics. New York: Wiley, 1981.
35. B. Horn and B. Schunck, "Determining optical flow," Artif. Intell., vol. 17, pp. 185-203, 1981.
36. J. Vermaak, A. Doucet, and P. Pérez, "Maintaining multi-modality through mixture tracking," in Proc. 9th IEEE Int. Conf. Computer Vision, Nice, France, Jun. 2003, pp. II:1110-1116.
37. K. Smith, D. Gatica-Perez, J. Odobez, and S. Ba, "Evaluating multiobject tracking," presented at the IEEE Conf. Computer Vision and Pattern Recognition, Workshop on Empirical Evaluation Methods in Computer Vision San Diego, CA, Jun. 2005.
38. C. Kervrann, F. Heitz, and P. Pérez, "Statistical model-based estimation and tracking of non-rigid motion," in Proc. 13th Int. Conf. Pattern Recognition, Vienna, Austria, Aug. 1996, pp. D:244-248.