TRACK AND CUT: SIMULTANEOUS TRACKING AND SEGMENTATION OF MULTIPLE OBJECTS WITH GRAPH CUTS

Aurélie Bugeau, Patrick Pérez

2008

Abstract

This paper presents a new method to both track and segment multiple objects in videos using min-cut/max-flow optimizations. We introduce objective functions that combine low-level pixel-wise measures (color, motion), high-level observations obtained via an independent detection module (connected components of foreground detection masks in the experiments), motion prediction and contrast-sensitive contextual regularization. One novelty is that external observations are used without adding any association step. The minimization of these cost functions simultaneously allows ”detection-before-track” tracking (track-to-observation assignment and automatic initialization of new tracks) and segmentation of tracked objects. When several tracked objects get mixed up by the detection module (e.g., single foreground detection mask for objects close to each other), a second stage of minimization allows the proper tracking and segmentation of these individual entities despite the observation confusion. Experiments on sequences from PETS 2006 corpus demonstrate the ability of the method to detect, track and precisely segment persons as they enter and traverse the field of view, even in cases of occlusions (partial or total), temporary grouping and frame dropping.

References

  1. Bertalmio, M., Sapiro, G., and Randall, G. (2000). Morphing active contours. IEEE Trans. Pattern Anal. Machine Intell., 22(7):733-737.
  2. Blake, A., Rother, C., Brown, M., Pérez, P., and Torr, P. (2004). Interactive image segmentation using an adaptive gmmrf model. In Proc. Europ. Conf. Computer Vision.
  3. Boykov, Y. and Jolly, M. (2001.). Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images. Proc. Int. Conf. Computer Vision.
  4. Boykov, Y., Veksler, O., and Zabih, R. (1998). Markov random fields with efficient approximations. In Proc. Conf. Comp. Vision Pattern Rec.
  5. Boykov, Y., Veksler, O., and Zabih, R. (2001). Fast approximate energy minimization via graph cuts. IEEE Trans. Pattern Anal. Machine Intell., 23(11):1222-1239.
  6. Comaniciu, D., Ramesh, V., and Meer, P. (2000). Realtime tracking of non-rigid objects using mean-shift. In Proc. Conf. Comp. Vision Pattern Rec.
  7. Comaniciu, D., Ramesh, V., and Meer, P. (2003). Kernelbased optical tracking. IEEE Trans. Pattern Anal. Machine Intell., 25(5):564-577.
  8. Cremers, D. and C. Schnörr, C. (2003). Statistical shape knowledge in variational motion segmentation. Image and Vision Computing, 21(1):77-86.
  9. Freedman, D. and Turek, M. (2005). Illumination-invariant tracking via graph cuts. Proc. Conf. Comp. Vision Pattern Rec.
  10. Isard, M. and Blake, A. (1998). Condensation - conditional density propagation for visual tracking. Int. J. Computer Vision, 29(1):5-28.
  11. Juan, O. and Boykov, Y. (2006). Active graph cuts. In Proc. Conf. Comp. Vision Pattern Rec.
  12. Kohli, P. and Torr, P. (2005). Effciently solving dynamic markov random fields using graph cuts. In Proc. Int. Conf. Computer Vision.
  13. Lucas, B. and Kanade, T. (1981). An iterative technique of image registration and its application to stereo. Proc. Int. Joint Conf. on Artificial Intelligence.
  14. Mansouri, A. (2002). Region tracking via level set pdes without motion computation. IEEE Trans. Pattern Anal. Machine Intell., 24(7):947-961.
  15. Paragios, N. and Deriche, R. (1999). Geodesic active regions for motion estimation and tracking. In Proc. Int. Conf. Computer Vision.
  16. Ronfard, R. (1994). Region-based strategies for active contour models. Int. J. Computer Vision, 13(2):229-251.
  17. Terzopoulos, D. and Szeliski, R. (1993). Tracking with kalman snakes. Active vision, pages 3-20.
  18. Wang, Y., Doherty, J., and Van Dyck, R. (2000). Moving object tracking in video. Applied Imagery Pattern Recognition (AIPR) Annual Workshop.
  19. Xu, N. and Ahuja, N. (2002). Object contour tracking using graph cuts based active contours. Proc. Int. Conf. Image Processing.
  20. Yilmaz, A. (2004). Contour-based object tracking with occlusion handling in video acquired using mobile cameras. IEEE Trans. Pattern Anal. Machine Intell., 26(11):1531-1536.
  21. Yilmaz, A., Javed, O., and Shah, M. (2006). Object tracking: A survey. ACM Comput. Surv., 38(4):13.
Download


Paper Citation


in Harvard Style

Bugeau A. and Pérez P. (2008). TRACK AND CUT: SIMULTANEOUS TRACKING AND SEGMENTATION OF MULTIPLE OBJECTS WITH GRAPH CUTS . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 447-454. DOI: 10.5220/0001075704470454


in Bibtex Style

@conference{visapp08,
author={Aurélie Bugeau and Patrick Pérez},
title={TRACK AND CUT: SIMULTANEOUS TRACKING AND SEGMENTATION OF MULTIPLE OBJECTS WITH GRAPH CUTS},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={447-454},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001075704470454},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - TRACK AND CUT: SIMULTANEOUS TRACKING AND SEGMENTATION OF MULTIPLE OBJECTS WITH GRAPH CUTS
SN - 978-989-8111-21-0
AU - Bugeau A.
AU - Pérez P.
PY - 2008
SP - 447
EP - 454
DO - 10.5220/0001075704470454