I. A. Ahmad and P. E. Lin, A nonparametric estimation of the entropy for absolutely continuous distributions (Corresp.), IEEE Transactions on Information Theory, vol.22, issue.3, pp.372-375, 1976.
DOI : 10.1109/TIT.1976.1055550

L. Alvarez, J. Weickert, and J. Sánchez, A scalespace approach to nonlocal optical flow calculations, International Conference on Scale-Space Theories in Computer Vision, 1999.

S. P. Awate and R. T. Whitaker, Unsupervised, information-theoretic, adaptive image filtering for image restoration, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.3, pp.364-376, 2006.
DOI : 10.1109/TPAMI.2006.64
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.2776

G. Aubert, M. Barlaud, O. Faugeras, and S. Jehan-besson, Image Segmentation Using Active Contours: Calculus of Variations or Shape Gradients?, SIAM Journal on Applied Mathematics, vol.63, issue.6, pp.2128-2145, 2003.
DOI : 10.1137/S0036139902408928
URL : https://hal.archives-ouvertes.fr/inria-00072105

M. J. Black and P. Anandan, The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields, Computer Vision and Image Understanding, vol.63, issue.1, pp.75-104, 1996.
DOI : 10.1006/cviu.1996.0006

S. Boltz, E. Debreuve, and M. Barlaud, Highdimensional statistical distance for region-ofinterest tracking: Application to combining a soft geometric constraint with radiometry, International Conference on Computer Vision and Pattern Recognition, 2007.

S. Boltz, A. Herbulot, E. Debreuve, and M. Barlaud, Entropy-based space-time segmentation in video sequences, ECCV Workshop on Statistical Methods in Multi-Image and Video Processing, 2006.

T. Brox, A. Bruhn, N. Papenberg, and J. Weickert, High Accuracy Optical Flow Estimation Based on a Theory for Warping, European Conference on Computer Vision, 2004.
DOI : 10.1007/978-3-540-24673-2_3

T. Brox, M. Rousson, R. Deriche, and J. Weickert, Unsupervised Segmentation Incorporating Colour, Texture, and Motion, International Conference on Computer Analysis of Images and Patterns, 2003.
DOI : 10.1007/978-3-540-45179-2_44
URL : https://hal.archives-ouvertes.fr/inria-00071826

A. Bruhn, J. Weickert, and C. Schnörr, Combining the Advantages of Local and Global Optic Flow Methods, DAGM Symposium on Pattern Recognition, 2002.
DOI : 10.1007/3-540-45783-6_55

V. Caselles, R. Kimmel, and G. Sapiro, Geodesic active contours, Proceedings of IEEE International Conference on Computer Vision, pp.61-79, 1997.
DOI : 10.1109/ICCV.1995.466871
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.21.2196

P. Charbonnier, L. Blanc-féraud, G. Aubert, and M. Barlaud, Deterministic edge-preserving regularization in computed imaging, IEEE Transactions on Image Processing, vol.6, issue.2, pp.298-311, 1997.
DOI : 10.1109/83.551699

D. Comaniciu, V. Ramesh, P. Meer, S. J. Osher, and S. Soatto, Real-time tracking of non-rigid objects using mean shift Kernel density estimation and intrinsic alignment for shape priors in level set segmentation, International Conference on Computer Vision and Pattern Recognition, pp.69335-351, 2000.

D. Cremers, M. Rousson, and R. Deriche, A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape, International Journal of Computer Vision, vol.18, issue.9, pp.195-215, 2007.
DOI : 10.1007/s11263-006-8711-1

D. Cremers and S. Soatto, Variational space-time motion segmentation, Proceedings Ninth IEEE International Conference on Computer Vision, 2003.
DOI : 10.1109/ICCV.2003.1238442
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.4850

D. Cremers and S. Soatto, Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation, International Journal of Computer Vision, vol.18, issue.9, pp.249-265, 2005.
DOI : 10.1007/s11263-005-4882-4

M. C. Delfour and J. Zolésio, Shapes and geometries: Analysis, differential calculus and optimization . Advances in Design and Control, Society for Industrial and Applied Mathematics, 2001.
DOI : 10.1137/1.9780898719826

C. C. Dórea, M. Pardàs, and F. Marqués, Generation of Long-Term Color and Motion Coherent Partitions, 2006 International Conference on Image Processing, 2006.
DOI : 10.1109/ICIP.2006.312402

A. Elgammal, R. Duraiswami, and L. S. Davis, Probabilistic tracking in joint feature-spatial spaces, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003.
DOI : 10.1109/CVPR.2003.1211432

D. Freedman and T. Zhang, Active Contours for Tracking Distributions, IEEE Transactions on Image Processing, vol.13, issue.4, pp.518-526, 2004.
DOI : 10.1109/TIP.2003.821445
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.11.5000

K. Fukunaga, Introduction to statistical pattern recognition, 1990.

M. N. Goria, N. N. Leonenko, V. V. Mergel, P. L. Novi, and . Inverardi, A new class of random vector entropy estimators and its applications in testing statistical hypotheses, Journal of Nonparametric Statistics, vol.27, issue.3, pp.277-297, 2005.
DOI : 10.2307/2285889

A. Herbulot, S. Boltz, E. Debreuve, and M. Barlaud, Robust Motion-Based Segmentation in Video Sequences using Entropy Estimator, 2006 International Conference on Image Processing, 2006.
DOI : 10.1109/ICIP.2006.312841

M. Hintermuller and W. Ring, A Second Order Shape Optimization Approach for Image Segmentation, SIAM Journal on Applied Mathematics, vol.64, issue.2, pp.442-467, 2004.
DOI : 10.1137/S0036139902403901

S. Jehan-besson, M. Barlaud, and G. Aubert, DREAM 2 S: deformable regions driven by an eulerian accurate minimization method for image and video segmentation, International Journal of Computer Vision, vol.53, issue.1, pp.45-70, 2003.
DOI : 10.1023/A:1023031708305
URL : https://hal.archives-ouvertes.fr/hal-00664596

J. Kim, J. W. Fisher, A. Yezzi, M. , and A. S. Willsky, A nonparametric statistical method for image segmentation using information theory and curve evolution, IEEE Trans. Image Process, vol.14, issue.10, pp.1486-1502, 2005.

M. Leventon, E. Grimson, and O. Faugeras, Statistical shape influence in geodesic active contour, International Conference on Computer Vision and Pattern Recognition, 2000.

M. E. Leventon, O. Faugeras, W. E. Grimson, W. M. Wells, and I. , Level set based segmentation with intensity and curvature priors, Workshop on Mathematical Methods in Biomedical Image Analysis, 2000.

B. D. Lucas and T. Kanade, An iterative image registration technique with an application to stereo vision, International Joint Conference on Artificial Intelligence, 1981.

A. Mittal and N. Paragios, Motion-based background subtraction using adaptive kernel density estimation, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004.
DOI : 10.1109/CVPR.2004.1315179
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.480

H. Neemwuchwala and A. O. Hero, Entropic Graphs for Registration, pp.185-235, 2005.
DOI : 10.1201/9781420026986.ch6

J. Odobez and P. Bouthemy, Robust Multiresolution Estimation of Parametric Motion Models, Journal of Visual Communication and Image Representation, vol.6, issue.4, pp.348-365, 1995.
DOI : 10.1006/jvci.1995.1029

N. Paragios and R. Deriche, Geodesic Active Regions: A New Framework to Deal with Frame Partition Problems in Computer Vision, Journal of Visual Communication and Image Representation, vol.13, issue.1-2, pp.249-2681065, 1962.
DOI : 10.1006/jvci.2001.0475

Y. Rubner, C. Tomasi, and L. J. Guibas, The earth mover's distance as a metric for image retrieval, International Journal of Computer Vision, vol.40, issue.2, pp.99-121, 2000.
DOI : 10.1023/A:1026543900054

C. Samson, L. Blanc-féraud, G. Aubert, and J. Zerubia, A Level Set Model for Image Classification, Int. J. Comput. Vision, vol.40, issue.3, pp.187-197, 2000.
DOI : 10.1007/3-540-48236-9_27

T. Schoenemann and D. Cremers, Near Real-Time Motion Segmentation Using Graph Cuts, DAGM Symposium on Pattern Recognition, 2006.
DOI : 10.1007/11861898_46
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.3822

D. W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization, 1992.
DOI : 10.1002/9781118575574

B. W. Silverman, Density Estimation for Statistics and Data Analysis, 1986.
DOI : 10.1007/978-1-4899-3324-9

J. Weickert and C. Schnörr, Variational optic flow computation with a spatio-temporal smoothness constraint, Journal of Mathematical Imaging and Vision, vol.14, issue.3, pp.245-255, 2001.
DOI : 10.1023/A:1011286029287

W. Wells, P. Viola, H. Atsumi, S. Nakajima, and R. Kikinis, Multi-modal volume registration by maximization of mutual information, Medical Image Analysis, vol.1, issue.1, pp.35-51, 1996.
DOI : 10.1016/S1361-8415(01)80004-9

S. F. Wu and J. Kittler, A Gradient-Based Method for General Motion Estimation and Segmentation, Journal of Visual Communication and Image Representation, vol.4, issue.1, pp.25-38, 1993.
DOI : 10.1006/jvci.1993.1003

A. Yezzi, A. Tsai, and A. Willsky, A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations, Journal of Visual Communication and Image Representation, vol.13, issue.1-2, p.195216, 2002.
DOI : 10.1006/jvci.2001.0500

S. Zhu and K. Ma, Correction to "A new diamond search algorithm for fast block-matching motion estimation", IEEE Transactions on Image Processing, vol.9, issue.3, pp.287-290, 2000.
DOI : 10.1109/TIP.2000.826791