M. Pham, Y. Gao, V. Hoang, C. , and T. , Fast polygonal integration and its application in extending haar-like features to improve object detection, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.942-949, 2010.
DOI : 10.1109/CVPR.2010.5540117
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.190.9370

Y. Boykov, O. Veksler, and R. Zabih, Markov random fields with efficient approximations, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231), 1998.
DOI : 10.1109/CVPR.1998.698673
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.3857

H. Ishikawa, Exact optimization for markov random fields with convex priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.10, p.25, 2003.
DOI : 10.1109/TPAMI.2003.1233908
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.106.8689

C. J. Geyer and J. Møller, Simulation Procedures and Likelihood Inference for Spatial Point Processes, Scandinavian Journal of Statistics, vol.21, issue.4, pp.359-373, 1994.

P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, issue.4, pp.711-732, 1995.
DOI : 10.1093/biomet/82.4.711

X. Descombes, R. Minlos, and E. Zhizhina, Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum, Journal of Mathematical Imaging and Vision, vol.21, issue.3, pp.347-359, 2009.
DOI : 10.1007/s10851-008-0117-y
URL : https://hal.archives-ouvertes.fr/inria-00422411

A. Gamal-eldin, X. Descombes, and J. Zerubia, Multiple Birth and Cut Algorithm for Point Process Optimization, 2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems, 2010.
DOI : 10.1109/SITIS.2010.17
URL : https://hal.archives-ouvertes.fr/inria-00516305

A. Gamal-eldin, X. Descombes, G. , C. Zerubia, and J. , A fast Multiple Birth and Cut algorithm using belief propagation, 2011 18th IEEE International Conference on Image Processing, 2011.
DOI : 10.1109/ICIP.2011.6116256
URL : https://hal.archives-ouvertes.fr/inria-00592446

C. Andrieu, N. De-freitas, A. Doucet, J. , and M. I. , An introduction to MCMC for machine learning, 2001.

C. Andrieu and A. Doucet, Joint Bayesian model selection and estimation of noisy sinusoids via reversible jump MCMC, IEEE Transactions on Signal Processing, vol.47, issue.10, pp.2667-2676, 1999.
DOI : 10.1109/78.790649
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.3283

G. Perrin, X. Descombes, J. Zerubia, and J. Boureau, Forest resource assessment using stochastic geometry, Proc. Int. Precision Forestry Symposium ], 2006.

H. Kesten, [Percolation Theory for Mathematicians, Prob. Statist, issue.2, 1982.
DOI : 10.1007/978-1-4899-2730-9
URL : http://projecteuclid.org/euclid.bia/1423514982

S. Descamps, X. Descombes, A. Béchet, and J. Zerubia, Automatic Flamingo detection using a multiple birth and death process, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008.
DOI : 10.1109/ICASSP.2008.4517809

V. S. Lempitsky and A. Zisserman, Learning to count objects in images, pp.1324-1332, 2010.

B. Hadj, S. Chatelain, F. Descombes, X. Zerubia, and J. , Parameter estimation for a marked point process within a framework of multidimensional shape extraction from remote sensing images, Proc. ISPRS Tech. Com. III, Symposium on Photogrammetry Computer Vision and Image Analysis, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00526345