Tracking by Shape with Deforming Prediction for Non-rigid Objects

Kenji Nishida, Takumi Kobayashi, Jun Fujiki

Abstract

A novel algorithm for tracking by shape with deforming prediction is proposed. The algorithm is based on the similarity of the predicted and actual object shape. Second order approximation for feature point movement by Taylor expansion is adopted for shape prediction, and the similarity is measured by using chamfer matching of the predicted and the actual shape. Chamfer matching is also used to detect the feature point movements to predict the object deformation. The proposed algorithm is applied to the tracking of a skier and showed a good tracking and shape prediction performance.

References

  1. Authors, submitted to VISAPP 2014.
  2. S.Avidan, “Ensemble Tracking”, IEEE PAMI, Vol.29, No.2, pp.261,271, 2007.
  3. D.Beymer, et al., “A Real-Time Computer Vision System for Measuring Traffic Parameters”, in Proc. IEEE CVPR, pp.495-501, 1997.
  4. T. Brox, C. Bregler, and J. Malik, “Large Displacement Optical Flow”, in Proc. CVPR 2009, pp. 41-48, 2009.
  5. B.Coifman, et al., “A Real-time Computer Vision System for Vehicle Tracking and Traffic surveillance”, Transportation Research Part C, No.6, pp.271-288, 1998.
  6. R.T.Collins, et al., “Online Selection of Discriminative Tracking Features”, in IEEE PAMI, Vol.27, No.10, pp.1631-1643, 2005.
  7. D. Comaniciu, V. Ramesh, and P. Meer,. “Real-Time Tracking of Non-Rigid Objects using Mean Shift”, in Proc. CVPR 2000, pp. 142-149, 2000.
  8. D.Comeniciu, P.Meer, “MeanShift: A Robust Approach Toward Feature Space Analysis”, IEEE PAMI, Vol.24, No.5, pp.603-619, May, 2002.
  9. D.M. Gavrila, “Pedestrian Detection from a Moving Vehicle”, in Proc. ECCV 2009, pp. 37-49, 2009.
  10. M. Godec, P.M Roth, and H.Bischof, “Hough-based Tracking on Non-rigid Objects”, to appear in J. of Computer Vision and Image Understanding, available online, Elsevier, 2013.
  11. H.Grabner, M.Grabner, H.Bischof, “Real-Time Tracking via On-line Boosting”, in Proc. BMVC, pp.47-56, 2006.
  12. H.Grabner, C.Leistner, H.Bischof, “Semi-Supervised OnLine Boosting for Robust Tracking”, in Proc. ECCV 2008, pp.234-247, 2008.
  13. D.Huttenlocher, G.Klanderman, and W.J.Rucklidge, “Comparing Images using the Hausdorff Distance”, in IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15, No. 9, pp. 850-863, 1993.
  14. Z.Kim, J.Malik, “Fast Vehicle Detection with Probabilistic Feature Grouping and its Application ot Vehicle Tracking”, in Proc. ICCV, pp.524-531 2003.
  15. D.Koller, J.Weber, J.Malik, “Robust Multiple Car Tracking with Occlusion Reasoning”, in proc. ECCV, Vol.A, pp.189-196, 1994.
  16. V.Mahadevan, N.Vasconcelos, “Salliency-based Discriminant Tracking”, in Proc.of CVPR 2009, pp.1007-1013, 2009.
  17. A. Mohan, C. Papageorgiou, and T. Poggio, “Examplebased Object Detection in Images by Components”, in IEEE Trans. Pattern Analysis and Machine Learning', Vol. 23, No. 4, pp. 349-361, 2001.
  18. K.F. Sim, and K. Sundaraj,. “Human Motion Tracking of Athlete Using Optical Flow & Artificial Markers”, in Proc. ICIAS 2010, pp. 1-4, 2010.
  19. G.Sundaramoorthi, A.Mennucci, S.Soatto, A.Yezzi, “A New Geometric Metric in the Space of Curves, and Applications to Tracking Deforming Objects by Prediction and Filtering”, in SIAM j. of Imaging Science, Vol.4, No.1, pp.109-145, 2010.
  20. T.Woodley, B.Stenger, R.Chipolla, “Tracking using Online Feature Selection and a Local Generative Model”, in Proc. BMVC 2007, 2007.
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Paper Citation


in Harvard Style

Nishida K., Kobayashi T. and Fujiki J. (2014). Tracking by Shape with Deforming Prediction for Non-rigid Objects . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 580-587. DOI: 10.5220/0004813305800587


in Bibtex Style

@conference{icpram14,
author={Kenji Nishida and Takumi Kobayashi and Jun Fujiki},
title={Tracking by Shape with Deforming Prediction for Non-rigid Objects},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={580-587},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004813305800587},
isbn={978-989-758-018-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Tracking by Shape with Deforming Prediction for Non-rigid Objects
SN - 978-989-758-018-5
AU - Nishida K.
AU - Kobayashi T.
AU - Fujiki J.
PY - 2014
SP - 580
EP - 587
DO - 10.5220/0004813305800587