High-dimensional statistical distance for region-of-interest tracking: Application to combining a soft geometric constraint with radiometry

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2007, Pages

  Boltz, Sylvain ^a   Debreuve, Eric ^a   Barlaud, Michel ^a  

^a UNIVERSITY OF NICE SOPHIA ANTIPOLIS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; GEOMETRY; IMAGE RECONSTRUCTION; PATTERN MATCHING; RADIOMETRY; STATISTICAL METHODS;

GEOMETRIC CONSTRAINTS; KULLBACK LEIBLER DISTANCES;

IMAGE ANALYSIS;

EID: 34948856944     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2007.383241     Document Type: Conference Paper

References (20)

1. I. Ahmad and P. E. Lin. A nonparametric estimation of the entropy for absolutely continuous distributions. IEEE Trans. Inform. Theory, 22(3):372- 375, 1976.
2. A. Banerjee, S. Merugu, I. Dhillon, and J. Ghosh. Clustering with bregman divergences. J. Mach. Learn. Res., 6:1705-1749, 2005.
3. S. Boltz, E. Wolsztynski, E. Debreuve, E. Thierry, M. Barlaud, and L. Pronzato. A minimum-entropy procedure for robust motion estimation. In ICIP, Atlanta, GA, October 2006.
4. T. Brox, M. Rousson, R. Deriche, and J. Weickert. Unsupervised segmentation incorporating colour, texture, and motion. In Computer Analysis of Images and Patterns, volume 2756 of LNCS, pages 353-360, Groningen, The Netherlands, 2003.
5. R. Collins, X. Zhou, and S. K. Teh. An open source tracking testbed and evaluation web site. In IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS), Breckenridge, CO, http://www. vividevaluation.ri.cmu.edu/, 2005.
6. D. Comaniciu, V. Ramesh, and P. Meer. Real-time tracking of non-rigid objects using mean shift. In CVPR, pages 142-151, Hilton Head Island, SC, 2000.
7. A. Elgammal, R. Duraiswami, and L. S. Davis. Probabilistic tracking in joint feature-spatial spaces. In CVPR, pages 781-788, Madison, WI, 2003.
8. K. Fukunaga. Introduction to statistical pattern recognition (2nd ed.). Academic Press Professional, Inc., 1990.
9. M. N. Goria, N. N. Leonenko, V. V. Mergel, and P. L. N. Inverardi. A new class of random vector entropy estimators and its applications in testing statistical hypotheses. J. Nonparametr. Stat., 17(3):277-297, 2005.
10. P. Huber. Robust Statistics. John Wiley and Sons, 1981.
11. L. Kozachenko and N. Leonenko. On statistical estimation of entropy of random vector. Problems Infor. Transmiss., 23(2):95-101, 1987.
12. N. Leonenko, L. Pronzato, and V. Savani. A class of Renyi information estimators for multidimensional densities. PASCAL archive: http://eprints. pascal-network.org/archive/00001031/, 2005.
13. P. Pérez, C. Hue, J. Vermaak, and M. Gangnet. Color-based probabilistic tracking. In ECCV, volume 2350 of LNCS, pages 661-675, Copenhaguen, Denmark, 2002.
14. D. Scott. Multivariate Density Estimation: Theory, Practice, and Visualization. Wiley, 1992.
15. B. Silverman. Density Estimation for Statistics and Data Analysis. Chapman and Hall, London, 1986.
16. R. Venkatesh Babu, P. Pérez, and P. Bouthemy. Robust tracking with motion estimation and local kernel-based color modeling. Image Vis. Comput. In Press, 2007.
17. P. Viola and W M. Wells. Alignment by maximization of mutual information. Int. J. Comput. Vis., 24(2):137-154, 1997.
18. J. Weickert and C. Schnörr. Variational optic flow computation with a spatio-temporal smoothness constraint. J. Math. Imaging Vis., 14(3):245-255, 2001.
19. C. Yang, R. Duraiswami, N. A. Gumerov, and L. Davis. Improved fast gauss transform and efficient kernel density estimation. In ICCV, Nice, France, 2003.
20. S. Zhu and K.-K. Ma. A new diamond search algorithm for fast block-matching motion estimation. IEEE Trans. Image Process., 9(2):287-290, 2000.