GENERIC OBJECT TRACKING FOR FAST VIDEO ANNOTATION

Rémi Trichet, Bernard Mérialdo

2007

Abstract

This article describes a method for fast video annotation using an object tracking technique. This work is part of the development of a system for interactive television, where video objects have to be identified in the video program. This environment puts specific requirements on the object tracking technique. We propose to use a generic technique based on keypoints. We describe three contributions in order to best satisfy those requirements: a model for a broader temporal use of the keypoints, an ambient color adaptation pre-treatment enhancing the keypoint detector performance, and a motion based bounding box repositioning algorithm. Finally, we present experimental results to validate those contributions.

References

  1. Comaniciu D., Meer P., 2002, Mean Shift: A Robust Approach Toward Feature Space Analysis, IEEE Trans. Pattern Anal. Mach. Intell. 24(5): 603-619.
  2. Dufournaud Y., Schmid C., Horaud R., June 2000, Matching Images with Different Resolutions, International Conference on Computer Vision & Pattern Recognition.
  3. Gabriel P., Hayet J.-B., Piater J., Verly J., 2005, Object Tracking Using Color Interest Points, in Proc. of the IEEE Int. Conf. on Advanced Video and Signal based Surveillance (AVSS'05).
  4. Gouet V., Oct 2000, Mise en correspondance d'images en couleur - Application à la synthèse de vues intermédiaires, Thèse de doctorat, Université de Montpellier II.
  5. Gyaourova A., Kamath C., and Cheung S.-C., October 2003, Block matching for object tracking, LLNL Technical report,. UCRL-TR-200271.
  6. Harris C., Stephens M.J., 1988, A combined corner and edge detector, In Alvey vision conference, pp147-152.
  7. Hu W., Tan T., Wang L., Aug 2004, M. S, A survey on visual surveillance of object motion and behaviors, IEEE Transactions on Systems, Man and Cybernetics, Part C, Vol. 34, No 3, pp. 334- 352.
  8. Isard M. and MacCormick J., 2001, BraMBLe: A Bayesian Multiple-Blob Tracker Proc Int. Conf. Computer Vision, vol. 2, 34-41.
  9. Jaffré G., Crouzil A, 2003, Non-rigid object localization from color model using mean shift, ICIP (3), 317-320.
  10. Karaulova IA, Hall P, Marshall A., 2000, A hierarchical model of dynamics for tracking people with a single video camera. In: Mirmehdi M, Thomas B, editors. Proceedings of the Eleventh British Machine Vision Conference (BMVC2000), p. 352--61. Bristol: ILES Press.
  11. Moravec, H.P, 1980, Obstacle avoidance and navigation in the real world by a seeing robot rover, Tech. Rept, CMU-RI-TR-3, The Robotic Institute, CarnegieMellon University, Pittsburgh, PA.
  12. Mikolajczyk K., Schmid C., May 2001, Indexation à l'aide de points d'intérêt invariants à l'échelle Journées ORASIS GDR-PRC Communication Homme-Machine.
  13. Mikolajczyk K., Schmid C., 2005-1, A performance evaluation of local descriptors, IEEE Transactions on Pattern Analysis & Machine Intelligence, Volume 27, Number 10.
  14. Mikolajczyk K., Tuytelaars T., Schmid C., Zisserman A., Matas J., Schaffalitzky F., Kadir F., Van Gool L., 2005-2, A comparison of affine region detectors, International Journal of Computer Vision, Volume 65, Number ½.
  15. Mindru F., Tuytelaars T., Van Gool L., Jul.2003, Moment Invariants for Recognition under Changing Viewpoint and Illumination, Theo Moons,ACM.
  16. Montesinos P., Gouet V., Deriche R., 1998, Differential invariants for color images, International conference on pattern recognition.
  17. Pupilli, M., and Calway, A., 2005, Real-Time Camera Tracking Using a Particle Filter, In Proceedings of the British Machine Vision Conference, BMVA Press.
  18. Schmid C. and Mohr R., 1997, Local Greyvalue Invariants for Image Retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence.
  19. Techmer A., 2001, Contour-based motion estimation and object tracking for real-time applications. In International Conference on Image Processing, volume 3, pages 648--651, Thessaloniki, Greece, 87.
Download


Paper Citation


in Harvard Style

Trichet R. and Mérialdo B. (2007). GENERIC OBJECT TRACKING FOR FAST VIDEO ANNOTATION . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 978-972-8865-74-0, pages 419-426. DOI: 10.5220/0002045104190426


in Bibtex Style

@conference{visapp07,
author={Rémi Trichet and Bernard Mérialdo},
title={GENERIC OBJECT TRACKING FOR FAST VIDEO ANNOTATION},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},
year={2007},
pages={419-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002045104190426},
isbn={978-972-8865-74-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
TI - GENERIC OBJECT TRACKING FOR FAST VIDEO ANNOTATION
SN - 978-972-8865-74-0
AU - Trichet R.
AU - Mérialdo B.
PY - 2007
SP - 419
EP - 426
DO - 10.5220/0002045104190426