S. Agarwal, N. Snavely, I. Simon, S. Seitz, and R. Szeliski, Building rome in a day, IEEE 12th International Conference on Computer Vision, pp.72-79, 2009.

C. Andrieu, A. Nando-de-freitas, M. I. Doucet, and . Jordan, 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

A. Baddeley, I. Barany, and R. Schneider, Spatial point processes and their applications, Stochastic Geometry, pp.1-75, 2007.

A. Baddeley and R. Turner, Modelling spatial point patterns in R. In Case Studies in Spatial Point Pattern Modelling, Lecture Notes in Statistics, vol.185, p.2374, 2006.

A. J. Baddeley and M. N. Van-lieshout, Stochastic geometry models in high-level vision, Journal of Applied Statistics, vol.55, issue.5-6, pp.5-6231, 1993.
DOI : 10.1098/rsta.1990.0127

H. Bay and A. Ess, Speeded-Up Robust Features (SURF), Computer Vision and Image Understanding, vol.110, issue.3, pp.346-359, 2008.
DOI : 10.1016/j.cviu.2007.09.014

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.738

A. Bechet, A. Reed, N. Plante, J. F. Giroux, and G. Gauthier, ESTIMATING THE SIZE OF THE GREATER SNOW GOOSE POPULATION, Journal of Wildlife Management, vol.59, issue.3, pp.639-649, 2004.
DOI : 10.2193/0022-541X(2004)068[0639:ETSOTG]2.0.CO;2

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

C. Benedek, X. Descombes, and J. Zerubia, Building Detection in a Single Remotely Sensed Image with a Point Process of Rectangles, 2010 20th International Conference on Pattern Recognition, 2010.
DOI : 10.1109/ICPR.2010.350

URL : https://hal.archives-ouvertes.fr/inria-00481019

J. Besag, Spatial Interaction and the Statistical Analysis of Lattice Systems, Journal of the Royal Statistical Society. Series B (Methodological), vol.36, issue.2, pp.192-236, 1974.

C. M. Bishop, Pattern Recognition and Machine Learning, 2006.

A. Blake, C. Rother, M. Brown, P. Perez, and P. Torr, Interactive Image Segmentation Using an Adaptive GMMRF Model, Proc. European Conference on Computer Vision (ECCV), 2004.
DOI : 10.1007/978-3-540-24670-1_33

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.980

R. Bogdan, A. Holzbach, N. Blodow, and M. Beetz, Fast Geometric Point Labeling using Conditional Random Fields, Proceedings of the 22nd IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2009.

Y. Boykov, Computing geodesics and minimal surfaces via graph cuts, Proceedings Ninth IEEE International Conference on Computer Vision, pp.26-33, 2003.
DOI : 10.1109/ICCV.2003.1238310

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.123.6433

Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max- flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.9, pp.1124-1137, 2004.
DOI : 10.1109/TPAMI.2004.60

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), pp.648-655, 1998.
DOI : 10.1109/CVPR.1998.698673

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.118.3857

Y. Boykov, O. Veksler, and R. Zabih, Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.11, pp.1222-1239, 2002.
DOI : 10.1109/34.969114

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.112.6806

W. Burgin, C. Pantofaru, and W. D. Smart, Using depth information to improve face detection, Proceedings of the 6th international conference on Human-robot interaction, HRI '11, pp.119-120, 2011.
DOI : 10.1145/1957656.1957690

F. Chatelain, X. Descombes, and J. Zerubia, Parameter estimation for marked point processes. application to object extraction from remote sensing images. (poster), Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2009.
URL : https://hal.archives-ouvertes.fr/hal-00391719

T. F. Cootes and C. J. Taylo, Statistical models of appearance for computer vision, Imaging Science and Biomedical Engineering, 2004.

T. H. Cormen, C. Stein, R. L. Rivest, and C. E. Leiserson, Introduction to Algorithms, 2009.

J. Neider, D. Shreiner, M. Woo, and T. Davis, OpenGL(R) Programming Guide, 2007.

D. J. Daley and D. V. Jones, An introduction to the theory of point processes, 2008.

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

S. Descamps, X. Descombes, A. Béchet, and J. Zerubia, Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations, Traitement du Signal, vol.26, issue.2, pp.95-108, 2009.

S. Descamps, M. Gauthier-clerc, J. Gendner, and Y. L. Maho, The annual breeding cycle of unbanded king penguins Aptenodytes patagonicus on Possession Island (Crozet), Avian Science, vol.2, pp.1-12, 2002.

X. Descombes, Stochastic Geometry for Image Analysis, 2011.
DOI : 10.1002/9781118601235

URL : https://hal.archives-ouvertes.fr/hal-00793677

X. Descombes, R. Minlos, and E. Zhizhina, Object extraction using a stochastic birthand-death dynamics in continuum, Research Report, vol.6135, 2007.

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

X. Descombes, M. Sigelle, and F. Preteux, Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing imaging, IEEE Transactions on Image Processing, vol.8, issue.4, pp.490-503, 1999.
DOI : 10.1109/83.753737

G. Dong and S. T. Acton, Detection of rolling leukocytes by marked point processes, Journal of Electronic Imaging, vol.16, issue.3, 2007.
DOI : 10.1117/1.2774829

M. Erikson, Two preprocessing techniques based on grey level and geometric thickness to improve segmentation results, Pattern Recognition Letters, vol.27, issue.3, pp.160-166, 2006.
DOI : 10.1016/j.patrec.2005.07.010

P. Muse, F. Cao, Y. Gousseau, P. Muse, and F. Sur, Unsupervised thresholds for shape matching, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), pp.647-650, 2003.
DOI : 10.1109/ICIP.2003.1246763

URL : https://hal.archives-ouvertes.fr/inria-00104270

M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang et al., Query by image and video content: the qbic system, Computer, issue.9, pp.2823-2855, 1995.

A. Gamal-eldin, X. Descombes, G. Charpiat, and J. Zerubia, 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

A. Gamal-eldin, X. Descombes, G. Charpiat, and J. Zerubia, Multiple birth and cut algorithm for multiple object detection, Journal of Multimedia Processing and Technologies, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00616371

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

M. G. Gauthier, Poles en peril, Buchet Chastel, 2007.

M. Gauthier-clerc, J. Gendner, C. Ribic, W. Fraser, E. J. Woehler et al., Long-term effects of flipper bands on penguins, Proceedings of the Royal Society B: Biological Sciences, vol.271, issue.Suppl_6, p.271
DOI : 10.1098/rsbl.2004.0201

W. Ge and R. T. Collins, Marked point processes for crowd counting, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206621

S. Geman and D. Geman, Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.6, issue.6, pp.721-741, 1984.

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

G. Gherdovich and X. Descombes, Two dof camera pose estimation with a planar stochastic reference grid, p.762, 2010.

W. R. Gilk, S. Richardson, and D. Spiegelhalter, Markov Chain Monte Carlo in Practice, 1995.

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

D. M. Greig, B. T. Porteous, and A. H. Seheult, Exact maximum a posteriori estimation for binary images, Journal of the Royal Statistical Society, vol.51, issue.2, pp.271-279, 1989.

J. Huang, S. R. Kumar, M. Mitra, W. Zhu, and R. Zabih, Image indexing using color correlograms. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, p.762, 1997.

H. Ishikawa, Exact optimization for markov random fields with convex priors, Proc. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), pp.1333-1336, 2003.
DOI : 10.1109/TPAMI.2003.1233908

H. Ishikawa and D. Geiger, Mapping image restoration to a graph problem, Proc. of IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, 1999.

M. J. Urban, O. Matas, T. Chum, and . Pajdla, Robust wide-baseline stereo from maximally stable extremal regions, Image Vision Computing, pp.761-767, 2004.

B. Eva, L. Jensen, and . Stougaard-nielsen, A review on inhomogeneous markov point processes, Lecture Notes-Monograph Series, vol.37, pp.297-318, 2001.

A. E. Johnson and M. Hebert, Using spin images for efficient object recognition in cluttered 3D scenes, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.5, pp.433-449, 1999.
DOI : 10.1109/34.765655

K. Karantzalos and N. Paragios, Recognition-Driven Two-Dimensional Competing Priors Toward Automatic and Accurate Building Detection, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.1, pp.133-144, 2009.
DOI : 10.1109/TGRS.2008.2002027

URL : http://dspace.lib.ntua.gr/handle/123456789/28630

H. Kesten, Percolation Theory for Mathematicians Number 2 in Progr, Prob. Statist. Birkhäuser, Mass, 1982.

V. Kettnaker and R. Zabih, Counting people from multiple cameras, Proceedings IEEE International Conference on Multimedia Computing and Systems, p.267, 1999.
DOI : 10.1109/MMCS.1999.778358

J. Kim, V. Kolmogorov, and R. Zabih, Visual correspondence using energy minimization and mutual information, Proc. International Conference on Computer Vision (ICCV), pp.1033-1040, 2003.

P. Kohli and P. H. Torr, Dynamic Graph Cuts for Efficient Inference in Markov Random Fields, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.12, pp.292079-208, 2007.
DOI : 10.1109/TPAMI.2007.1128

V. Kolmogorov and R. Zabih, What energy functions can be minimized via graph cuts?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, issue.2, pp.147-159, 2004.
DOI : 10.1109/TPAMI.2004.1262177

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.113.1823

M. S. Kulikova, I. H. Jermyn, X. Descombes, E. Zhizhina, and J. Zerubia, Extraction of arbitrarily-shaped objects using stochastic multiple birth-and-death dynamics and active contours, Computational Imaging VIII, 2010.
DOI : 10.1117/12.839191

URL : https://hal.archives-ouvertes.fr/inria-00465472

G. L. David, Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, vol.60, pp.91-110, 2004.

C. Lacoste, X. Descombes, and J. Zerubia, A comparative study of point processes for line network extraction in remote sensing, Research Report, vol.4516, 2002.
URL : https://hal.archives-ouvertes.fr/inria-00072072

T. Lindeberg, Scale-space theory: a basic tool for analyzing structures at different scales, Journal of Applied Statistics, vol.21, issue.1, pp.224-270, 1994.
DOI : 10.1080/757582976

Y. Liu, O. Veksler, and O. Juan, Simulating Classic Mosaics with Graph Cuts, Proc. Energy Minimization Methods in Computer Vision and Pattern Recognition (EMM- CVPR), pp.55-70, 2007.
DOI : 10.1007/978-3-540-74198-5_5

A. Lorette, X. Descombes, and J. Zerubia, Texture analysis through a markovian modelling and fuzzy classification: Application to urban area extraction from satellite images, International Journal of Computer Vision, vol.36, issue.3, pp.221-236, 2000.
DOI : 10.1023/A:1008129103384

G. David and . Lowe, Object recognition from local scale-invariant features, International Conference on Computer Vision (ICCV), pp.1150-1157, 1999.

K. Mikolajczyk and C. Schmid, Indexing based on scale invariant interest points, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.525-531, 2001.
DOI : 10.1109/ICCV.2001.937561

URL : https://hal.archives-ouvertes.fr/inria-00548276

K. Mikolajczyk and C. Schmid, Scale & Affine Invariant Interest Point Detectors, International Journal of Computer Vision, vol.60, issue.1, pp.63-86, 2004.
DOI : 10.1023/B:VISI.0000027790.02288.f2

URL : https://hal.archives-ouvertes.fr/inria-00548554

K. Mikolajczyk, C. Schmid, and A. Zisserman, Human Detection Based on a Probabilistic Assembly of Robust Part Detectors, pp.434-444, 2009.
DOI : 10.1007/978-3-540-24670-1_6

URL : https://hal.archives-ouvertes.fr/inria-00548537

J. Moller and R. P. Waagepetersen, Statistical Inference and Simulation for Spatial Point Processes, 2004.
DOI : 10.1201/9780203496930

N. Paragios, Y. Chen, and O. Faugeras, Handbook of Mathematical Models in Computer Vision, 2005.
DOI : 10.1007/0-387-28831-7

J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, 1988.

G. Perrin, X. Descombes, and J. Zerubia, 2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes, 18th International Conference on Pattern Recognition (ICPR'06), 2006.
DOI : 10.1109/ICPR.2006.20

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

R. Pflugfelder and H. Bischof, Localization and Trajectory Reconstruction in Surveillance Cameras with Nonoverlapping Views, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.4, pp.709-721, 2009.
DOI : 10.1109/TPAMI.2009.56

P. Christian, G. Robert, and . Casella, Monte Carlo Statistical Methods, 1999.

J. , L. Rodgers, and W. A. Nicewander, Thirteen ways to look at the correlation coefficient, The American Statistician, vol.42, issue.1, pp.59-66, 1988.

S. Roy and I. J. Cox, A maximum-flow formulation of the N-camera stereo correspondence problem, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), p.492, 1998.
DOI : 10.1109/ICCV.1998.710763

R. B. Rusu, N. Blodow, and M. Beetz, Fast Point Feature Histograms (FPFH) for 3D registration, 2009 IEEE International Conference on Robotics and Automation, pp.3212-3217, 2009.
DOI : 10.1109/ROBOT.2009.5152473

N. Thongsak, S. Tongphu, and M. N. Dailey, Rapid detection of many object instances, 2004.

C. Saraux, C. L. Bohec, M. Joel, . Durant, A. Vincent et al., Reliability of flipper-banded penguins as indicators of climate change, Nature, issue.7329, pp.471203-206, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00555723

R. Stoica, X. Descombes, and J. Zerubia, A Gibbs Point Process for Road Extraction from Remotely Sensed Images, International Journal of Computer Vision, vol.57, issue.2, pp.121-136, 2004.
DOI : 10.1023/B:VISI.0000013086.45688.5d

D. Stoyan and H. Stoyan, Fractals, random shapes, and point fields, 1994.

M. Stricker, A. Dimai, and E. Dimai, Color indexing with weak spatial constraints, Proc. SPIE Storage and Retrieval for Image and Video Databases, pp.29-40, 1996.

A. Tayebi and S. Mcgilvray, Attitude stabilization of a VTOL quadrotor aircraft, IEEE Transactions on Control Systems Technology, vol.14, issue.3, pp.562-571, 2006.
DOI : 10.1109/TCST.2006.872519

M. N. Van-lieshout, Markov Point Processes and Their Applications, 2000.
DOI : 10.1142/p060

P. Viola, M. J. Jones, and D. Snow, Detecting pedestrians using patterns of motion and appearance. Computer Vision, 2003.

A. Paul, M. J. Viola, and . Jones, Robust real-time face detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004.

B. Wu and R. Nevatia, Detection of multiple, partially occluded humans in a single image by bayesian combination of edgelet part detectors, Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV), pp.90-97, 2005.

B. Zhan, D. Monekosso, P. Remagnino, S. Velastin, and L. Xu, Crowd analysis: a survey, Machine Vision and Applications, pp.345-357, 1007.
DOI : 10.1007/s00138-008-0132-4

. Abstract, First part: ???? We proposed a novel probabilistic approach to handle occlusions and perspective effects (challenging problems in computer vision) for 3D object detection from a 2D image. The proposed method is based on 3D scene simulation on the GPU using OpenGL. Candidates configurations are proposed, simulated on the GPU and projected onto the image plane. Configurations are modified until convergence using an appropriate optimization algorithm. Second part: ????? We proposed a new optimization method for Point Process models, which is a interesting framework for solving many challenging problems dealing with high resolution images. Our optimization method which we call " Multiple Births and Cut " (MBC), is the only semideterministic optimiser for the point process models. Our proposed algorithm overcomes all previously existing optimisers in terms of: speed, simplicity, reduced and simplified set of parameters