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Optics Letters

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  • Editor: Alan E. Willner
  • Vol. 33, Iss. 21 — Nov. 1, 2008
  • pp: 2521–2523

Stochastic complexity integral image based technique for fast video tracking

Jean-François Boulanger, Frédéric Galland, Pascal Martin, and Philippe Réfrégier  »View Author Affiliations


Optics Letters, Vol. 33, Issue 21, pp. 2521-2523 (2008)
http://dx.doi.org/10.1364/OL.33.002521


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Abstract

We propose a new method based on the minimization of the stochastic complexity for fast and efficient tracking adapted to video images with a static camera. The obtained criterion combines the advantages of background-subtraction-based techniques and those of using measures of similarities to a target model without requiring any tuning of a weighting parameter. It is then demonstrated that this approach can be implemented with a fast integral image technique to estimate the location and the rectangular shape of the target in a few milliseconds.

© 2008 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(110.4280) Imaging systems : Noise in imaging systems
(100.4999) Image processing : Pattern recognition, target tracking

ToC Category:
Image Processing

History
Original Manuscript: July 22, 2008
Manuscript Accepted: September 17, 2008
Published: October 28, 2008

Citation
Jean-François Boulanger, Frédéric Galland, Pascal Martin, and Philippe Réfrégier, "Stochastic complexity integral image based technique for fast video tracking," Opt. Lett. 33, 2521-2523 (2008)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-33-21-2521


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References

  1. J. Rissanen, Stochastic Complexity in Statistical Inquiry, Vol. 15 of Series in Computer Science (World Scientific, 1989).
  2. P. Viola and M. Jones, in IEEE Conference on Computer Vision and Pattern Recognition (IEEE, 2000), p. 511.
  3. C. Stauffer and W. E. L. Grimson, IEEE Trans. Pattern Anal. Mach. Intell. 22, 747 (2000). [CrossRef]
  4. Y. Sheikh and M. Shah, IEEE Trans. Pattern Anal. Mach. Intell. 27, 1778 (2005). [CrossRef] [PubMed]
  5. L. Li, W. Huang, I. Yu-Hua Gu, and Q. Tian, IEEE Trans. Image Process. 13, 1459 (2004). [CrossRef]
  6. M. Isard and A. Blake, International J. Comp. Vis. 29, 5 (1998).
  7. D. Comaniciu, V. Ramesh, and P. Meer, IEEE Trans. Pattern Anal. Mach. Intell. 25, 564 (2003). [CrossRef]
  8. B. Zhang, W. Tian, and Z. Jin, Chin. Opt. Lett. 4, 569 (2006).
  9. R. Han, Z. Jing, and Y. Li, Chin. Opt. Lett. 6, 168 (2008). [CrossRef]
  10. O. Ruch and P. Réfrégier, Opt. Lett. 26, 977 (2001). [CrossRef]
  11. H.-L. Shen and J. H. Xin, Opt. Lett. 32, 96 (2007). [CrossRef]

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