Improved proposal distribution with gradient measures for tracking

2005 IEEE Workshop on Machine Learning for Signal Processing

Volumn , Issue , 2005, Pages 105-110

  Brasnett, Paul ^a   Mihaylova, Lyudmila ^a   Bull, David ^a   Canagarajah, Nishan ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

OBJECT TRACKING; PARTICLE FILTERS; PROPOSAL DISTRIBUTION;

COMPUTATIONAL COMPLEXITY; DATA PROCESSING; LEARNING SYSTEMS; OBJECT RECOGNITION; OPTIMIZATION; SIGNAL PROCESSING;

PROBABILITY DISTRIBUTIONS;

EID: 33749045673     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2005.1532883     Document Type: Conference Paper

References (12)

1. M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp, "A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking," IEEE Trans. on Signal Proc., vol. 50, no. 2, pp. 174-188, 2002.
2. J. Liu and R. Chen, "Sequential Monte Carlo methods for dynamic systems," Journal of the American Statistical Association, vol. 93, no. 443, pp. 1032-1044, 1998.
3. N. Gordon, D. Salmond, and A. Smith, "A novel approach to nonlinear / non-Gaussian Bayesian state estimation," IEE Proc. on Radar and Signal Processing, vol. 40, pp. 107-113, 1993.
4. A. Doucet, S. Godsill, and C. Andrieu, "On sequential Monte Carlo sampling methods for Bayesian filtering," Statistics and Computing, vol. 10, no. 3, pp. 197-208, 2000.
5. S. Haykin, K. Huber, and Z. Chen, "Bayesian sequential state estimation for MIMO wireless communications," Proceedings of the IEEE, vol. 92, no. 3, pp. 439-454, March 2004.
6. J. Sullivan and J. Rittscher, "Guiding random particles by deterministic search," in IEEE Int. Conf. on Computer Vision, July 2001, vol. 1, pp. 323-330.
7. C. Chang and R. Ansari, "Kernel particle filter for visual tracking," IEEE Signal Processing Letters, vol. 12, no. 3, pp. 242-245, March 2005.
8. D. Comaneciu, V. Ramesh, and P. Meer, "Kernel-based object tracking," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 564-577, 2003.
9. A. Kong, J. Liu, and W. Wong, "Sequential imputations and Bayesian missing data problems," Journal of the American Statistical Association, vol. 89, pp. 278-288, 1994.
10. P. Pérez, J. Vermaak, and A. Blake, "Data fusion for tracking with particles," Proceedings of the IEEE, vol. 92, no. 3, pp. 495-513, March 2004.
11. G. D. Hager and P. N. Belhumeur, "Efficient region tracking with parametric models of geometry and illumination," IEEE Trans. on PAMI, vol. 20, no. 10, pp. 1025-1039, 1998.
12. Y. Bar-Shalom and X.R. Li, Estimation and Tracking: Principles, Techniques and Software, Artech House, 1993.