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

M. Barzohar and D. Cooper, Automatic finding of main roads in aerial images by using geometric-stochastic models and estimation. T-PAMI, 1996.

F. Chatelain, X. Descombes, F. Lafarge, C. Lantuejoul, C. Mallet et al., Stochastic Geometry for Image Analysis, 2011.

E. Galin, A. Peytavie, N. Marechal, and E. Guerin, Procedural Generation of Roads, Eurographics, 2010.
DOI : 10.1111/j.1467-8659.2009.01612.x

URL : https://hal.archives-ouvertes.fr/hal-01381447

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

J. Hu, A. Razdan, J. Femiani, M. Cui, and P. Wonka, Road Network Extraction and Intersection Detection From Aerial Images by Tracking Road Footprints, IEEE Transactions on Geoscience and Remote Sensing, vol.45, issue.12, p.45, 2007.
DOI : 10.1109/TGRS.2007.906107

C. Lacoste, X. Descombes, and J. Zerubia, Point process for unsupervised line network extraction in remote sensing. T-PAMI, 2005.

F. Lafarge, G. Gimelfarb, and X. Descombes, Geometric feature extraction by a multi-marked point process. T-PAMI, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00503140

D. Lesage, E. D. Angelini, I. Bloch, and G. Funka-lea, A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes, Medical Image Analysis, vol.13, issue.6, 2009.
DOI : 10.1016/j.media.2009.07.011

D. Marin, A. Aquino, M. Gegundez-arias, and J. Bravo, A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features, IEEE Transactions on Medical Imaging, vol.30, issue.1, 2011.
DOI : 10.1109/TMI.2010.2064333

H. Mayer, I. Laptev, and A. Baumgartner, Multi-scale and snakes for automatic road extraction, ECCV, 1998.
DOI : 10.1007/BFb0055700

J. Mckeown, D. M. , and J. Denlinger, Cooperative methods for road tracking in aerial imagery, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 1988.
DOI : 10.1109/CVPR.1988.196307

T. P. Minka, Estimating a Dirichlet distribution, 2003.

V. Mnih and G. Hinton, Learning to detect roads in highresolution aerial images, ECCV, 2010.

M. Pechaud, R. Keriven, and G. Peyre, Extraction of tubular structures over an orientation domain, 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009.
DOI : 10.1109/CVPR.2009.5206782

URL : https://hal.archives-ouvertes.fr/hal-00365599

T. Peng, I. Jermyn, V. Prinet, and J. Zerubia, Extended Phase Field Higher-Order Active Contour Models for??Networks, International Journal of Computer Vision, vol.27, issue.4, 2008.
DOI : 10.1007/s11263-009-0304-3

URL : https://hal.archives-ouvertes.fr/inria-00503900

C. Poullis and S. You, Delineation and geometric modeling of road networks, ISPRS Journal of Photogrammetry and Remote Sensing, vol.65, issue.2, p.2010
DOI : 10.1016/j.isprsjprs.2009.10.004

M. Rochery, I. Jermyn, and J. Zerubia, Higher Order Active Contours, International Journal of Computer Vision, vol.24, issue.12, p.69, 2006.
DOI : 10.1007/s11263-006-6851-y

URL : https://hal.archives-ouvertes.fr/inria-00070352

E. Turetken, F. Benmansour, and P. Fua, Automated reconstruction of tree structures using path classifiers and Mixed Integer Programming, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012.
DOI : 10.1109/CVPR.2012.6247722

Y. Verdie and F. Lafarge, Efficient Monte Carlo Sampler for Detecting Parametric Objects in Large Scenes, 2007.
DOI : 10.1007/978-3-642-33712-3_39

URL : https://hal.archives-ouvertes.fr/hal-00742770

R. Wang and Y. Zhang, Extraction of urban road network using quickbird pan-sharpened multispectral and panchromatic imagery by performing edge-aided post-classification, IS- PRS, p.8, 2003.

Z. Yu, V. Prinet, C. Pan, and P. Chen, A novel two-steps strategy for automatic gis-image registration, ICIP, p.8, 2004.