A SIMPLE DERIVATION TO IMPLEMENT TRACKING DISTRIBUTIONS

Wei Yu, Jifeng Ning, Jiong Zhang, Nan Geng

Abstract

We present a simple and straightforward derivation to implement active contours for tracking distributions (Freedman and Zhang, 2004) and its improvement, i.e., distribution tracking through background mismatch (Zhang and Freedman, 2005). In the original work, two steps are performed in order to derive the tracking evolution equations. In the first step, curve flows are derived using Green’s Theorem, and in the second step level set method is used to implement the curve flows, which seems to be somewhat complex. In our implementation, tracking evolution equations are derived directly by using variational theory. This is useful to understand the tracking method better. The final tracking evolution equations are identical to the previous work (Freedman and Zhang, 2004; Zhang and Freedman, 2005).

References

  1. Allili, M. S. and Ziou, D. (2007). Active contours for video object tracking using region, boundary and shape information. Signal, Image and Video Processing, 1(2):101-117.
  2. Bibby, C. and Reid, I. (2008). Robust real-time visual tracking using pixel-wise posteriors. Proceedings of the European Conference on Computer Vision (ECCV) 2008, page 831-844.
  3. Chan, T. F. and Vese, L. A. (2001). Active contours without edges. IEEE Transactions on Image Processing, 10(2):266-277.
  4. Cremers, D. (2006). Dynamical statistical shape priors for level set-based tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, page 1262-1273.
  5. Freedman, D. and Zhang, T. (2004). Active contours for tracking distributions. IEEE Transactions on Image Processing, 13(4):518-526.
  6. Fussenegger, M., Deriche, R., and Pinz, A. (2006). Multiregion level set tracking with transformation invariant shape priors. Proceedings of Asian Conference on Computer Vision 2006, page 674-683.
  7. Li, C., Kao, C., Gore, J., and Ding, Z. (2007). Implicit active contours driven by local binary fitting energy. In 2007 IEEE Conference on Computer Vision and Pattern Recognition, page 1-7.
  8. Osher, S. and Sethian, J. A. (1988). Fronts propagating with curvature-dependent speed: algorithms based on hamilton-jacobi formulations. Journal of Computational Physics, 79(1):12-49.
  9. Prisacariu, V. and Reid, I. (2011). Nonlinear shape manifolds as shape priors in level set segmentation and tracking.
  10. Vese, L. A. and Chan, T. F. (2002). A multiphase level set framework for image segmentation using the mumford and shah model. International Journal of Computer Vision, 50(3):271-293.
  11. Wei-chang, Q. (1980). Calculus of variations and finite element [M]. Beijing: Science Press.
  12. Zhang, K., Song, H., and Zhang, L. (2010). Active contours driven by local image fitting energy. Pattern Recognition, 43(4):1199-1206.
  13. Zhang, T. and Freedman, D. (2005). Improving performance of distribution tracking through background mismatch. IEEE transactions on pattern analysis and machine intelligence, page 282-287.
  14. Zhou, X., Hu, W., and Li, X. (2007). An adaptive shape subspace model for level set-based object tracking. In Subspace 2007. Workshop on Asian Conference on Computer Vision, page 9-16.
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Paper Citation


in Harvard Style

Yu W., Ning J., Zhang J. and Geng N. (2012). A SIMPLE DERIVATION TO IMPLEMENT TRACKING DISTRIBUTIONS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 351-354. DOI: 10.5220/0003816603510354


in Bibtex Style

@conference{visapp12,
author={Wei Yu and Jifeng Ning and Jiong Zhang and Nan Geng},
title={A SIMPLE DERIVATION TO IMPLEMENT TRACKING DISTRIBUTIONS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={351-354},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003816603510354},
isbn={978-989-8565-04-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - A SIMPLE DERIVATION TO IMPLEMENT TRACKING DISTRIBUTIONS
SN - 978-989-8565-04-4
AU - Yu W.
AU - Ning J.
AU - Zhang J.
AU - Geng N.
PY - 2012
SP - 351
EP - 354
DO - 10.5220/0003816603510354