Ketut Fundana, Niels Chr. Overgaard, Anders Heyden, David Gustavsson, Mads Nielsen


We address the problem of nonrigid object segmentation in image sequences in the presence of occlusions. The proposed variational segmentation method is based on a region-based active contour of the Chan-Vese model augmented with a frame-to-frame interaction term as a shape prior. The interaction term is constructed to be pose-invariant by minimizing over a group of transformations and to allow moderate deformation in the shape of the contour. The segmentation method is then coupled with a novel variational contour matching formulation between two consecutive contours which gives a mapping of the intensities from the interior of the previous contour to the next. With this information occlusions can be detected and located using deviations from predicted intensities and the missing intensities in the occluded regions can be reconstructed. After reconstructing the occluded regions in the novel image, the segmentation can then be improved. Experimental results on synthetic and real image sequences are shown.


  1. Andresen, P. R. and Nielsen, M. (1999). Non-rigid registration by geometry-constrained diffusion. In Taylor, C. and et al, editors, MICCAI'99, LNCS 1679, pages 533-543. Springer Verlag.
  2. Bresson, X., Vandergheynst, P., and Thiran, J.-P. (2006). A variational model for object segmentation using boundary information and shape prior driven by the mumford-shah functional. International Journal of Computer Vision, 68(2):145-162.
  3. Caselles, V., Kimmel, R., and Sapiro, G. (1997). Geodesic active contours. International Journal of Computer Vision, 22(1):61-79.
  4. Chan, T. and Vese, L. (2001). Active contour without edges. IEEE Transactions on Image Processing, 10(2):266- 277.
  5. Chan, T. and Zhu, W. (2005). Level set based prior segmentation. In Proceeding CVPR 2005, volume 2, pages 1164-1170.
  6. Chen, Y., Tagare, H. D., Thiruvenkadam, S., Huang, F., Wilson, D., Gopinath, K. S., Briggs, R. W., and Geiser, E. A. (2002). Using prior shapes in geometric active contours in a variational framework. International Journal of Computer Vision, 50(3):315-328.
  7. Cremers, D. and Funka-Lea, G. (2005). Dynamical statistical shape priors for level set based sequence segmentation. In Paragios, N. and et al., editors, 3rd Workshop on Variational and Level Set Methods in Computer Vision, LNCS 3752, pages 210-221. Springer Verlag.
  8. Cremers, D. and Soatto, S. (2003). A pseudo-distance for shape priors in level set segmentation. In Faugeras, O. and Paragios, N., editors, 2nd IEEE Workshop Cremers, D., Sochen, N., and Schnörr, C. (2003). Towards recognition-based variational segmentation using shape priors and dynamic labeling. In Griffin, L. and Lillholm, M., editors, Scale Space 2003, LNCS 2695, pages 388-400. Springer Verlag.
  9. Gentile, C., Camps, O., and Sznaier, M. (2004). Segmentation for robust tracking in the presence of severe occlusion. IEEE Transactions on Image Processing, 13(2):166-178.
  10. Gustavsson, D., Fundana, K., Overgaard, N. C., Heyden, A., and Nielsen, M. (2007). Variational segmentation and contour matching of non-rigid moving object. In ICCV Workshop on Dynamical Vision 2007, LNCS. Springer Verlag.
  11. Konrad, J. and Ristivojevic, M. (2003). Video segmentation and occlusion detection over multiple frames. In Vasudev, B., Hsing, T. R., Tescher, A. G., and Ebrahimi, T., editors, Image and Video Communications and Processing 2003, SPIE 5022, pages 377-388. SPIE.
  12. Leventon, M., Grimson, W., and Faugeras, O. Statistical shape influence in geodesic active contours. In Proc. Int'l Conf. Computer Vision and Pattern Recognition, pages 316-323.
  13. Osher, S. and Fedkiw, R. (2003). Level Set Methods and Dynamic Implicit Surfaces. Springer-Verlag, New York.
  14. Paragios, N., Rousson, M., and Ramesh, V. (2003). Matching Distanve Functions: A Shape-to-Area Variational Approach for Global-to-Local Registration. In Heyden, A. and et al, editors, ECCV 2002, LNCS 2351, pages 775-789. Springer-Verlag Berlin Heidelberg.
  15. Riklin-Raviv, T., Kiryati, N., and Sochen, N. (2007). Priorbased segmentation and shape registration in the presence of perspective distortion. International Journal of Computer Vision, 72(3):309-328.
  16. Rousson, M. and Paragios, N. (2002). Shape priors for level set representations. In Heyden, A. and et al, editors, ECCV 2002, LNCS 2351, pages 78-92. Springer Verlag.
  17. Solem, J. E. and Overgaard, N. C. (2005). A geometric formulation of gradient descent for variational problems with moving surfaces. In Kimmel, R., Sochen, N., and Weickert, J., editors, Scale-Space 2005, volume 3459 of LNCS, pages 419-430. Springer Verlag.
  18. Strecha, C., Fransens, R., and Gool, L. V. (2004). A probabilistic approach to large displacement optical flow and occlusion detection. In Statistical Methods in Video Processing, LNCS 3247, pages 71-82. Springer Verlag.
  19. Thiruvenkadam, S. R., Chan, T. F., and Hong, B.-W. (2007). Segmentation under occlusions using selective shape prior. In Scale Space and Variational Methods in Computer Vision, volume 4485 of LNCS, pages 191- 202. Springer Verlag.
  20. Tsai, A., Yezzy, A., Wells, W., Tempany, C., Tucker, D., Fan, A., Grimson, W. W., and Willsky, A. (2003). A shape-based approach to the segmentation of medical imagery using level sets. IEEE Transactions on Medical Imaging, 22(2):137-154.

Paper Citation

in Harvard Style

Fundana K., Chr. Overgaard N., Heyden A., Gustavsson D. and Nielsen M. (2008). NONRIGID OBJECT SEGMENTATION AND OCCLUSION DETECTION IN IMAGE SEQUENCES . 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 211-218. DOI: 10.5220/0001076102110218

in Bibtex Style

author={Ketut Fundana and Niels Chr. Overgaard and Anders Heyden and David Gustavsson and Mads Nielsen},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},

in EndNote Style

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
SN - 978-989-8111-21-0
AU - Fundana K.
AU - Chr. Overgaard N.
AU - Heyden A.
AU - Gustavsson D.
AU - Nielsen M.
PY - 2008
SP - 211
EP - 218
DO - 10.5220/0001076102110218