| Year |
Citation |
Score |
| 2016 |
Bressloff PC, Ermentrout B, Faugeras O, Thomas PJ. Stochastic Network Models in Neuroscience: A Festschrift for Jack Cowan. Introduction to the Special Issue. Journal of Mathematical Neuroscience. 6: 4. PMID 27043152 DOI: 10.1186/s13408-016-0036-y |
0.6 |
|
| 2015 |
Bossy M, Faugeras O, Talay D. Clarification and Complement to "Mean-Field Description and Propagation of Chaos in Networks of Hodgkin-Huxley and FitzHugh-Nagumo Neurons". Journal of Mathematical Neuroscience. 5: 31. PMID 26329321 DOI: 10.1186/s13408-015-0031-8 |
0.6 |
|
| 2015 |
Veltz R, Chossat P, Faugeras O. On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1. Journal of Mathematical Neuroscience. 5: 23. PMID 26055523 DOI: 10.1186/s13408-015-0023-8 |
0.6 |
|
| 2015 |
Fasoli D, Faugeras O, Panzeri S. A formalism for evaluating analytically the cross-correlation structure of a firing-rate network model. Journal of Mathematical Neuroscience. 5: 6. PMID 25852981 DOI: 10.1186/s13408-015-0020-y |
0.6 |
|
| 2015 |
Faugeras O, Inglis J. Stochastic neural field equations: a rigorous footing. Journal of Mathematical Biology. 71: 259-300. PMID 25069787 DOI: 10.1007/s00285-014-0807-6 |
0.6 |
|
| 2015 |
Faugeras O, MacLaurin J. Asymptotic description of neural networks with correlated synaptic weights Entropy. 17: 4701-4743. DOI: 10.3390/e17074701 |
0.6 |
|
| 2014 |
Faugeras O, Thieullen M. Editorial for the special issue on uncertainty in the brain. Journal of Mathematical Neuroscience. 4: 7. PMID 24742109 DOI: 10.1186/2190-8567-4-7 |
0.6 |
|
| 2014 |
Rankin J, Meso AI, Masson GS, Faugeras O, Kornprobst P. Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration. Journal of Computational Neuroscience. 36: 193-213. PMID 24014258 DOI: 10.1007/s10827-013-0465-5 |
0.6 |
|
| 2014 |
Faugeras O, MacLaurin J. A large deviation principle and an expression of the rate function for a discrete stationary Gaussian process Entropy. 16: 6722-6738. DOI: 10.3390/e16126722 |
0.6 |
|
| 2014 |
Faugeras O, MacLaurin J. A representation of the relative entropy with respect to a diffusion process in terms of its infinitesimal generator Entropy. 16: 6705-6721. DOI: 10.3390/e16126705 |
0.6 |
|
| 2014 |
Faugeras O, Maclaurin J. Asymptotic description of stochastic neural networks. I. Existence of a large deviation principle Comptes Rendus Mathematique. 352: 841-846. DOI: 10.1016/j.crma.2014.08.018 |
0.6 |
|
| 2014 |
Faugeras O, Maclaurin J. Asymptotic description of stochastic neural networks. II. Characterization of the limit law Comptes Rendus Mathematique. 352: 847-852. DOI: 10.1016/j.crma.2014.08.017 |
0.6 |
|
| 2013 |
Rankin J, Tlapale E, Veltz R, Faugeras O, Kornprobst P. Bifurcation analysis applied to a model of motion integration with a multistable stimulus. Journal of Computational Neuroscience. 34: 103-24. PMID 22870848 DOI: 10.1007/s10827-012-0409-5 |
0.6 |
|
| 2013 |
Veltz R, Faugeras O. A center manifold result for delayed neural fields equations Siam Journal On Mathematical Analysis. 45: 1527-1562. DOI: 10.1137/110856162 |
0.6 |
|
| 2012 |
Baladron J, Fasoli D, Faugeras O, Touboul J. Mean-field description and propagation of chaos in networks of Hodgkin-Huxley and FitzHugh-Nagumo neurons. Journal of Mathematical Neuroscience. 2: 10. PMID 22657695 DOI: 10.1186/2190-8567-2-10 |
0.6 |
|
| 2012 |
Galtier MN, Faugeras OD, Bressloff PC. Hebbian learning of recurrent connections: a geometrical perspective. Neural Computation. 24: 2346-83. PMID 22594830 DOI: 10.1162/NECO_a_00322 |
0.6 |
|
| 2012 |
Touboul J, Hermann G, Faugeras O. Noise-induced behaviors in neural mean field dynamics Siam Journal On Applied Dynamical Systems. 11: 49-81. DOI: 10.1137/110832392 |
0.6 |
|
| 2012 |
Baladron Pezoa J, Fasoli D, Faugeras O. Three applications of GPU computing in neuroscience Computing in Science and Engineering. 14: 40-47. DOI: 10.1109/MCSE.2011.119 |
0.6 |
|
| 2012 |
Faugeras O. Neural fields models of visual areas: Principles, successes, and caveats Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7583: 474-479. DOI: 10.1007/978-3-642-33863-2_48 |
0.6 |
|
| 2011 |
Touboul J, Wendling F, Chauvel P, Faugeras O. Neural mass activity, bifurcations, and epilepsy. Neural Computation. 23: 3232-86. PMID 21919787 DOI: 10.1162/NECO_a_00206 |
0.6 |
|
| 2011 |
Touboul JD, Faugeras OD. A Markovian event-based framework for stochastic spiking neural networks. Journal of Computational Neuroscience. 31: 485-507. PMID 21499739 DOI: 10.1007/s10827-011-0327-y |
0.6 |
|
| 2011 |
Deneux T, Faugeras O, Takerkart S, Masson GS, Vanzetta I. A new variational method for erythrocyte velocity estimation in wide-field imaging in vivo. Ieee Transactions On Medical Imaging. 30: 1527-45. PMID 21427018 DOI: 10.1109/TMI.2011.2131151 |
0.6 |
|
| 2011 |
Chossat P, Faye G, Faugeras O. Bifurcation of hyperbolic planforms Journal of Nonlinear Science. 21: 465-498. DOI: 10.1007/s00332-010-9089-3 |
0.6 |
|
| 2011 |
Tlapale E, Kornprobst P, Masson GS, Faugeras O. A Neural Field Model for Motion Estimation Springer Proceedings in Mathematics. 5: 159-179. DOI: 10.1007/978-3-642-19604-1_9 |
0.6 |
|
| 2010 |
Deneux T, Faugeras O. EEG-fMRI fusion of paradigm-free activity using Kalman filtering. Neural Computation. 22: 906-48. PMID 20028225 DOI: 10.1162/neco.2009.05-08-793 |
0.6 |
|
| 2010 |
Veitz R, Faugeras O. Local/global analysis of the stationary solutions of some neural field equations Siam Journal On Applied Dynamical Systems. 9: 954-998. DOI: 10.1137/090773611 |
0.6 |
|
| 2010 |
Faye G, Faugeras O. Some theoretical and numerical results for delayed neural field equations Physica D: Nonlinear Phenomena. 239: 561-578. DOI: 10.1016/j.physd.2010.01.010 |
0.6 |
|
| 2009 |
Chossat P, Faugeras O. Hyperbolic planforms in relation to visual edges and textures perception. Plos Computational Biology. 5: e1000625. PMID 20046839 DOI: 10.1371/journal.pcbi.1000625 |
0.6 |
|
| 2009 |
Faugeras O, Veltz R, Grimbert F. Persistent neural states: stationary localized activity patterns in nonlinear continuous n-population, q-dimensional neural networks. Neural Computation. 21: 147-87. PMID 19431281 DOI: 10.1162/neco.2008.12-07-660 |
0.6 |
|
| 2009 |
Faugeras O, Touboul J, Cessac B. A constructive mean-field analysis of multi-population neural networks with random synaptic weights and stochastic inputs. Frontiers in Computational Neuroscience. 3: 1. PMID 19255631 DOI: 10.3389/neuro.10.001.2009 |
0.6 |
|
| 2008 |
Touboul J, Faugeras O. A characterization of the first hitting time of double integral processes to curved boundaries Advances in Applied Probability. 40: 501-528. DOI: 10.1239/aap/1214950214 |
0.6 |
|
| 2007 |
Touboul J, Faugeras O. The spikes trains probability distributions: a stochastic calculus approach. Journal of Physiology, Paris. 101: 78-98. PMID 18054210 DOI: 10.1016/j.jphysparis.2007.10.008 |
0.6 |
|
| 2007 |
Kybic J, Faugeras O, Clerc M, Papadopoulo T. Neural mass model parameter identification for MEG/EEG Progress in Biomedical Optics and Imaging - Proceedings of Spie. 6511. DOI: 10.1117/12.709146 |
0.6 |
|
| 2007 |
Charpiat G, Faugeras O, Keriven R. Shape statistics for image segmentation with prior Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. DOI: 10.1109/CVPR.2007.383009 |
0.6 |
|
| 2007 |
Charpiat G, Maurel P, Pons JP, Keriven R, Faugeras O. Generalized gradients: Priors on minimization flows International Journal of Computer Vision. 73: 325-344. DOI: 10.1007/s11263-006-9966-2 |
0.6 |
|
| 2007 |
Pons JP, Keriven R, Faugeras O. Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score International Journal of Computer Vision. 72: 179-193. DOI: 10.1007/s11263-006-8671-5 |
0.6 |
|
| 2006 |
Grimbert F, Faugeras O. Bifurcation analysis of Jansen's neural mass model. Neural Computation. 18: 3052-68. PMID 17052158 DOI: 10.1162/neco.2006.18.12.3052 |
0.6 |
|
| 2006 |
Deneux T, Faugeras O. Using nonlinear models in fMRI data analysis: model selection and activation detection. Neuroimage. 32: 1669-89. PMID 16844388 DOI: 10.1016/j.neuroimage.2006.03.006 |
0.6 |
|
| 2006 |
Kybic J, Clerc M, Faugeras O, Keriven R, Papadopoulo T. Generalized head models for MEG/EEG: boundary element method beyond nested volumes. Physics in Medicine and Biology. 51: 1333-46. PMID 16481698 DOI: 10.1088/0031-9155/51/5/021 |
0.6 |
|
| 2006 |
Maurel P, Keriven R, Faugeras O. Reconciling landmarks and level sets Proceedings - International Conference On Pattern Recognition. 4: 69-72. DOI: 10.1109/ICPR.2006.979 |
0.6 |
|
| 2006 |
Prados E, Camilli F, Faugeras O. A viscosity solution method for shape-from-shading without image boundary data Mathematical Modelling and Numerical Analysis. 40: 393-412. DOI: 10.1051/m2an:2006018 |
0.6 |
|
| 2006 |
Pons JP, Hermosillo G, Keriven R, Faugeras O. Maintaining the point correspondence in the level set framework Journal of Computational Physics. 220: 339-354. DOI: 10.1016/j.jcp.2006.05.036 |
0.6 |
|
| 2006 |
Paragios N, Faugeras O. International Journal of Computer Vision: Editorial International Journal of Computer Vision. 69: 5-6. DOI: 10.1007/s11263-006-6860-x |
0.6 |
|
| 2006 |
Prados E, Camilli F, Faugeras O. A unifying and rigorous shape from shading method adapted to realistic data and applications Journal of Mathematical Imaging and Vision. 25: 307-328. DOI: 10.1007/s10851-006-6899-x |
0.6 |
|
| 2006 |
Lenglet C, Rousson M, Deriche R, Faugeras O. Statistics on the manifold of multivariate normal distributions: Theory and application to diffusion tensor MRI processing Journal of Mathematical Imaging and Vision. 25: 423-444. DOI: 10.1007/s10851-006-6897-z |
0.6 |
|
| 2006 |
Pons JP, Keriven R, Faugeras O. Modelling non-rigid dynamic scenes from multi-view image sequences Handbook of Mathematical Models in Computer Vision. 439-452. DOI: 10.1007/0-387-28831-7_27 |
0.6 |
|
| 2006 |
Prados E, Faugeras O. Shape from shading Handbook of Mathematical Models in Computer Vision. 375-388. DOI: 10.1007/0-387-28831-7_23 |
0.6 |
|
| 2006 |
Paragios N, Chen Y, Faugeras O. Handbook of mathematical models in computer vision Handbook of Mathematical Models in Computer Vision. 1-605. DOI: 10.1007/0-387-28831-7 |
0.6 |
|
| 2006 |
Charpiat G, Faugeras O, Keriven R, Maurel P. Distance-based shape statistics Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 5: V925-V928. |
0.6 |
|
| 2006 |
Vanzetta I, Deneux T, Masson G, Faugeras O. Cerebral blood flow recorded at high sensitivity in two dimensions using high resolution optical imaging 2006 3rd Ieee International Symposium On Biomedical Imaging: From Nano to Macro - Proceedings. 2006: 1264-1267. |
0.6 |
|
| 2006 |
Deneux T, Faugeras O. EEG-fMRI fusion of non-triggered data using Kalman filtering 2006 3rd Ieee International Symposium On Biomedical Imaging: From Nano to Macro - Proceedings. 2006: 1068-1071. |
0.6 |
|
| 2005 |
Lenglet C, Rousson M, Deriche R, Faugeras O, Lehericy S, Ugurbil K. A Riemannian approach to diffusion tensor images segmentation. Information Processing in Medical Imaging : Proceedings of the ... Conference. 19: 591-602. PMID 17354728 |
0.6 |
|
| 2005 |
Kybic J, Clerc M, Faugeras O, Keriven R, Papadopoulo T. Fast multipole acceleration of the MEG/EEG boundary element method. Physics in Medicine and Biology. 50: 4695-710. PMID 16177498 DOI: 10.1088/0031-9155/50/19/018 |
0.6 |
|
| 2005 |
Kybic J, Clerc M, Abboud T, Faugeras O, Keriven R, Papadopoulo T. A common formalism for the integral formulations of the forward EEG problem. Ieee Transactions On Medical Imaging. 24: 12-28. PMID 15638183 DOI: 10.1109/TMI.2004.837363 |
0.6 |
|
| 2005 |
Charpiat G, Keriven R, Pons JP, Faugeras O. Designing spatially coherent minimizing flows for variational problems based on active contours Proceedings of the Ieee International Conference On Computer Vision. 1403-1408. DOI: 10.1109/ICCV.2005.69 |
0.6 |
|
| 2005 |
Charpiat G, Faugeras O, Keriven R. Image statistics based on diffeomorphic matching Proceedings of the Ieee International Conference On Computer Vision. 852-857. DOI: 10.1109/ICCV.2005.118 |
0.6 |
|
| 2005 |
Prados E, Faugeras O. Shape from shading: A well-posed problem? Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2: 870-877. DOI: 10.1109/CVPR.2005.319 |
0.6 |
|
| 2005 |
Pons JP, Keriven R, Faugeras O. Modelling dynamic scenes by registering multi-view image sequences Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2: 822-827. DOI: 10.1109/CVPR.2005.227 |
0.6 |
|
| 2005 |
Charpiat G, Faugeras O, Keriven R. Approximations of shape metrics and application to shape warping and empirical shape statistics Foundations of Computational Mathematics. 5: 1-58. DOI: 10.1007/s10208-003-0094-x |
0.6 |
|
| 2005 |
Paragios N, Faugeras O, Chan T, Schnoerr C. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics: Preface Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3752: V. |
0.6 |
|
| 2004 |
Thirion B, Faugeras O. Feature characterization in fMRI data: the Information Bottleneck approach. Medical Image Analysis. 8: 403-19. PMID 15567705 DOI: 10.1016/j.media.2004.09.001 |
0.6 |
|
| 2004 |
Faugeras O, Adde G, Charpiat G, Chefd'hotel C, Clerc M, Deneux T, Deriche R, Hermosillo G, Keriven R, Kornprobst P, Kybic J, Lenglet C, Lopez-Perez L, Papadopoulo T, Pons JP, et al. Variational, geometric, and statistical methods for modeling brain anatomy and function. Neuroimage. 23: S46-55. PMID 15501100 DOI: 10.1016/j.neuroimage.2004.07.015 |
0.6 |
|
| 2004 |
Faugeras O, Hermosillo G. Well-posedness of two nonrigid multimodal image registration methods Siam Journal On Applied Mathematics. 64: 1550-1587. DOI: 10.1137/S0036139903424904 |
0.6 |
|
| 2004 |
Chefd'hotel C, Tschumperlé D, Deriche R, Faugeras O. Regularizing Flows for Constrained Matrix-Valued Images Journal of Mathematical Imaging and Vision. 20: 147-162. DOI: 10.1023/B:JMIV.0000011324.14508.fb |
0.6 |
|
| 2004 |
Thirion B, Faugeras O. Dynamical components analysis of FMRI data: A second order solution Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2809: 552-563. DOI: 10.1007/978-3-540-45210-2_50 |
0.6 |
|
| 2004 |
Peeters RR, Kornprobst P, Nikolova M, Sunaert S, Vieville T, Malandain G, Deriche R, Faugeras O, Ng M, Van Hecke P. The use of super-resolution techniques to reduce slice thickness in functional MRI International Journal of Imaging Systems and Technology. 14: 131-138. DOI: 10.1002/ima.20016 |
0.6 |
|
| 2004 |
Thirion B, Faugeras O. Nonlinear dimension reduction of fMri data: The laplacian embedding approach 2004 2nd Ieee International Symposium On Biomedical Imaging: Macro to Nano. 1: 372-375. |
0.6 |
|
| 2004 |
Prados E, Faugeras O. Unifying approaches and removing unrealistic assumptions in shape from shading: Mathematics can help Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3024: 141-154. |
0.6 |
|
| 2004 |
Lenglet C, Deriche R, Faugeras O. Inferring white matter geometry from diffusion tensor MRI: Application to connectivity mapping Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3024: 127-140. |
0.6 |
|
| 2004 |
Kokkinos I, Deriche R, Maragos P, Faugeras O. A Biologically Motivated and Computationally Tractable Model of Low and Mid-Level Vision Tasks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3022: 506-517. |
0.6 |
|
| 2004 |
Pons JP, Keriven R, Faugeras O. Area preserving cortex unfolding Lecture Notes in Computer Science. 3216: 376-383. |
0.6 |
|
| 2003 |
Adde G, Clerc M, Faugeras O, Keriven R, Kybic J, Papadopoulo T. Symmetric BEM formulation for the M/EEG forward problem. Information Processing in Medical Imaging : Proceedings of the ... Conference. 18: 524-35. PMID 15344485 |
0.6 |
|
| 2003 |
Thirion B, Faugeras O. Dynamical components analysis of fMRI data through kernel PCA. Neuroimage. 20: 34-49. PMID 14527568 DOI: 10.1016/S1053-8119(03)00316-1 |
0.6 |
|
| 2003 |
Fize D, Vanduffel W, Nelissen K, Denys K, Chef d'Hotel C, Faugeras O, Orban GA. The retinotopic organization of primate dorsal V4 and surrounding areas: A functional magnetic resonance imaging study in awake monkeys. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 23: 7395-406. PMID 12917375 |
0.6 |
|
| 2003 |
Aubert G, Barlaud M, Faugeras O, Jehan-Besson S. Image segmentation using active contours: Calculus of variations or shape gradients? Siam Journal On Applied Mathematics. 63: 2128-2154. DOI: 10.1137/S0036139902408928 |
0.6 |
|
| 2003 |
Gomes J, Faugeras O. The vector distance functions International Journal of Computer Vision. 52: 161-187. DOI: 10.1023/A:1022956108418 |
0.6 |
|
| 2003 |
Charpiat G, Faugeras O, Keriven R. Shape metrics, warping and statistics Ieee International Conference On Image Processing. 2: 627-630. |
0.6 |
|
| 2003 |
Pons JP, Hermosillo G, Keriven R, Faugeras O. How to deal with point correspondences and tangential velocities in the level set framework Proceedings of the Ieee International Conference On Computer Vision. 2: 894-899. |
0.6 |
|
| 2003 |
Pons JP, Keriven R, Faugeras O, Hermosillo G. Variational stereovision and 3D scene flow estimation with statistical similarity measures Proceedings of the Ieee International Conference On Computer Vision. 1: 597-602. |
0.6 |
|
| 2003 |
Jehan-Besson S, Barlaud M, Aubert G, Faugeras O. Shape gradients for histogram segmentation using active contours Proceedings of the Ieee International Conference On Computer Vision. 1: 408-415. |
0.6 |
|
| 2003 |
Prados E, Faugeras O. "Perspective shape from shading" and viscosity solutions Proceedings of the Ieee International Conference On Computer Vision. 2: 826-831. |
0.6 |
|
| 2003 |
Thirion B, Faugeras O. Feature detection in fMRI data: The information bottleneck approach Lecture Notes in Computer Science. 2879: 83-91. |
0.6 |
|
| 2002 |
Hermosillo G, Chefd C, Faugeras O. Variational methods for multimodal image matching International Journal of Computer Vision. 50: 329-343. DOI: 10.1023/A:1020830525823 |
0.6 |
|
| 2002 |
Faugeras O, Perona P, Sapiro G. Special issue on partial differential equations in image processing, computer vision, and computer graphics Journal of Visual Communication and Image Representation. 13: 1-2. DOI: 10.1006/jvci.2002.0505 |
0.6 |
|
| 2002 |
Prados E, Faugeras O, Rouy E. Shape from shading and viscosity solutions Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2351: 790-804. |
0.6 |
|
| 2002 |
Chefd’Hotel C, Tschumperlé D, Deriche R, Faugeras O. Constrained flows of matrix-valued functions: Application to diffusion tensor regularization Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2350: 251-265. |
0.6 |
|
| 2001 |
Lorigo LM, Faugeras OD, Grimson WE, Keriven R, Kikinis R, Nabavi A, Westin CF. CURVES: curve evolution for vessel segmentation. Medical Image Analysis. 5: 195-206. PMID 11524226 DOI: 10.1016/S1361-8415(01)00040-8 |
0.6 |
|
| 2001 |
Delamarre Q, Faugeras O. 3D articulated models and multiview tracking with physical forces Computer Vision and Image Understanding. 81: 328-357. DOI: 10.1006/cviu.2000.0892 |
0.6 |
|
| 2001 |
Thirion B, Faugeras O. Revisiting non-parametric activation detection on fMRI time series Proceedings of the Workshop On Mathematical Methods in Biomedical Image Analysis. 121-128. |
0.6 |
|
| 2001 |
Hermosillo G, Faugeras O. Dense image matching with global and local statistical criteria: A variational approach Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 1: I73-I78. |
0.6 |
|
| 2001 |
Devernay F, Faugeras O. Straight lines have to be straight Machine Vision and Applications. 13: 14-24. |
0.6 |
|
| 2001 |
Gomes J, Faugeras O. Using the vector distance functions to evolve manifolds of arbitrary codimension Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2106: 1-13. |
0.6 |
|
| 2000 |
Faugeras O, Quan L, Strum P. Self-calibration of a 1D projective camera and its application to the self-calibration of a 2D projective camera Ieee Transactions On Pattern Analysis and Machine Intelligence. 22: 1179-1185. DOI: 10.1109/34.879801 |
0.6 |
|
| 2000 |
Gomes J, Faugeras O. Reconciling distance functions and level sets Journal of Visual Communication and Image Representation. 11: 209-223. DOI: 10.1006/jvci.1999.0439 |
0.6 |
|
| 2000 |
Gomes J, Faugeras O. Segmentation of the inner and outer surfaces of the human cortex: An approach based on partial differential equations Annual International Conference of the Ieee Engineering in Medicine and Biology - Proceedings. 3: 1764-1774. |
0.6 |
|
| 2000 |
Gomes J, Faugeras O. Level sets and distance functions Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1842: 588-602. |
0.6 |
|
| 2000 |
Anandan P, Faugeras O, Hartley R, Malik J, Mundy J. Summary of the panel session Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1883: 376-382. |
0.6 |
|
| 1999 |
Csurka G, Faugeras O. Algebraic and geometric tools to compute projective and permutation invariants Ieee Transactions On Pattern Analysis and Machine Intelligence. 21: 58-65. DOI: 10.1109/34.745735 |
0.6 |
|
| 1999 |
Gomes J, Faugeras O. Segmentation of the inner and outer surfaces of the cortex in man and monkey: An approach based on Partial Differential Equations Neuroimage. 9: S152. |
0.6 |
|
| 1999 |
Hermosillo G, Faugeras O, Gomes J. Unfolding the cerebral cortex using level set methods Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1682: 58-69. |
0.6 |
|
| 1998 |
Faugeras O, Keriven R. Variational principles, surface evolution, PDE's, level set methods, and the stereo problem. Ieee Transactions On Image Processing : a Publication of the Ieee Signal Processing Society. 7: 336-44. PMID 18276253 DOI: 10.1109/83.661183 |
0.6 |
|
| 1998 |
Delamarre Q, Faugeras O. Finding pose of hand in video images: A stereo-based approach Proceedings - 3rd Ieee International Conference On Automatic Face and Gesture Recognition, Fg 1998. 585-590. DOI: 10.1109/AFGR.1998.671011 |
0.6 |
|
| 1998 |
Papadopoulo T, Faugeras O. A new characterization of the trifocal tensor Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1406: 109-123. DOI: 10.1007/BFb0055662 |
0.6 |
|
| 1998 |
Faugeras O, Papadopoulo T. Nonlinear method for estimating the projective geometry of 3 views Proceedings of the Ieee International Conference On Computer Vision. 477-484. |
0.6 |
|
| 1998 |
Luong QT, Faugeras OD. On the Determination of Epipoles Using Cross-Ratios Computer Vision and Image Understanding. 71: 1-18. |
0.6 |
|
| 1998 |
Faugeras O, Papadopoulo T. Grassmann-Cayley algebra for modelling systems of cameras and the algebraic equations of the manifold of trifocal tensors Philosophical Transactions of the Royal Society a: Mathematical, Physical and Engineering Sciences. 356: 1123-1152. |
0.6 |
|
| 1998 |
Faugeras O, Robert L, Laveau S, Csurka G, Zeller C, Gauclin C, Zoghlami I. 3-D Reconstruction of Urban Scenes from Image Sequences Computer Vision and Image Understanding. 69: 292-309. |
0.6 |
|
| 1998 |
Csurka G, Faugeras O. Computing three dimensional project invariants from a pair of images using the Grassmann-Cayley algebra Image and Vision Computing. 16: 3-12. |
0.6 |
|
| 1997 |
Deriche R, Bouvin C, Faugeras OD. A level-set approach for stereo Proceedings of Spie - the International Society For Optical Engineering. 2942: 150-161. DOI: 10.1117/12.267171 |
0.6 |
|
| 1997 |
Navab N, Faugeras OD. The critical sets of lines for camera displacement estimation: A mixed euclidean-projective and constructive approach International Journal of Computer Vision. 23: 17-44. |
0.6 |
|
| 1997 |
Luong QT, Faugeras OD. Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices International Journal of Computer Vision. 22: 261-289. |
0.6 |
|
| 1997 |
Csurka G, Zeller C, Zhang Z, Faugeras OD. Characterizing the Uncertainty of the Fundamental Matrix Computer Vision and Image Understanding. 68: 18-36. |
0.6 |
|
| 1997 |
Rothwell C, Faugeras O, Csurka G. A Comparison of Projective Reconstruction Methods for Pairs of Views Computer Vision and Image Understanding. 68: 37-58. |
0.6 |
|
| 1997 |
Zoghlami I, Faugeras O, Deriche R. Using geometric corners to build a 2D mosaic from a set of images Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 420-425. |
0.6 |
|
| 1996 |
Zhang Z, Luong QT, Faugeras O. Motion of an uncalibrated stereo rig: Self-calibration and metric reconstruction Ieee Transactions On Robotics and Automation. 12: 103-113. DOI: 10.1109/70.481754 |
0.6 |
|
| 1996 |
Viéville T, Faugeras OD. The first order expansion of motion equations in the uncalibrated case Computer Vision and Image Understanding. 64: 128-146. DOI: 10.1006/cviu.1996.0049 |
0.6 |
|
| 1996 |
Luong QT, Faugeras OD. The fundamental matrix: Theory, algorithms, and stability analysis International Journal of Computer Vision. 17: 43-75. |
0.6 |
|
| 1996 |
Viéville T, Faugeras O, Luong QT. Motion of points and lines in the uncalibrated case International Journal of Computer Vision. 17: 7-41. |
0.6 |
|
| 1996 |
Leymarie F, de la Fortelle A, Koenderink JJ, Kappers AML, Stavridi M, van Ginneken B, Muller S, Krake S, Faugeras O, Robert L, Gauclin C, Laveau S, Zeller C. Realise: reconstruction of reality from image sequences Ieee International Conference On Image Processing. 3: 651-654. |
0.6 |
|
| 1996 |
Faugeras O, Robert L. What can two images tell us about a third one? International Journal of Computer Vision. 18: 5-19. |
0.6 |
|
| 1996 |
Laveau S, Faugeras O. Oriented projective geometry for computer vision Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1064: 147-156. |
0.6 |
|
| 1995 |
Zhang Z, Deriche R, Faugeras O, Luong QT. A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry Artificial Intelligence. 78: 87-119. DOI: 10.1016/0004-3702(95)00022-4 |
0.6 |
|
| 1995 |
Faugeras O, Mourrain B. About the correspondences of points between N images Proceedings of the Ieee Workshop On Representation of Visual Scenes. 37-44. |
0.6 |
|
| 1995 |
Rothwell C, Csurka G, Faugeras O. Comparison of projective reconstruction methods for pairs of views Ieee International Conference On Computer Vision. 932-937. |
0.6 |
|
| 1995 |
Vieville T, Faugeras OD. Motion analysis with a camera with unknown, and possibly varying intrinsic parameters Ieee International Conference On Computer Vision. 750-756. |
0.6 |
|
| 1994 |
Viéville T, Faugeras O. Robust and fast computation of edge characteristics in image sequences International Journal of Computer Vision. 13: 153-179. DOI: 10.1007/BF01427150 |
0.6 |
|
| 1994 |
Zhang Z, Faugeras OD. Finding Planes and Clusters of Objects from 3D Line Segments with Application to 3D Motion Determination Computer Vision and Image Understanding. 60: 267-284. DOI: 10.1006/cviu.1994.1063 |
0.6 |
|
| 1994 |
Zeller C, Faugeras O. Applications of non-metric vision to some visual guided tasks Intelligent Vehicles Symposium, Proceedings. 351-356. |
0.6 |
|
| 1994 |
Devernay F, Faugeras OD. Computing differential properties of 3-D shapes from stereoscopic images without 3-D models Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 208-213. |
0.6 |
|
| 1993 |
Faugeras O, Papadopoulo T. A theory of the motion fields of curves International Journal of Computer Vision. 10: 125-156. DOI: 10.1007/BF01420734 |
0.6 |
|
| 1993 |
Faugeras O. Computer vision research at INRIA International Journal of Computer Vision. 10: 91-99. DOI: 10.1007/BF01420732 |
0.6 |
|
| 1993 |
Luong QT, Faugeras OD. Determining the Fundamental matrix with planes: instability and new algorithms Ieee Computer Vision and Pattern Recognition. 489-494. |
0.6 |
|
| 1993 |
Vieville T, Romann F, Hotz B, Mathieu H, Buffa M, Robert L, Facao PEDS, Faugeras OD, Audren JT. Autonomous navigation of a mobile robot using inertial and visual cues 1993 International Conference On Intelligent Robots and Systems. 360-367. |
0.6 |
|
| 1992 |
Zhang Z, Faugeras OD. Estimation of Displacements from Two 3-D Frames Obtained from Stereo Ieee Transactions On Pattern Analysis and Machine Intelligence. 14: 1141-1156. DOI: 10.1109/34.177380 |
0.6 |
|
| 1992 |
Vaillant R, Faugeras OD. Using Extremal Boundaries for 3-D Object Modeling Ieee Transactions On Pattern Analysis and Machine Intelligence. 14: 157-173. DOI: 10.1109/34.121787 |
0.6 |
|
| 1992 |
Maybank SJ, Faugeras OD. A theory of self-calibration of a moving camera International Journal of Computer Vision. 8: 123-151. DOI: 10.1007/BF00127171 |
0.6 |
|
| 1992 |
Zhang Z, Faugeras OD. Three-dimensional motion computation and object segmentation in a long sequence of stereo frames International Journal of Computer Vision. 7: 211-241. DOI: 10.1007/BF00126394 |
0.6 |
|
| 1992 |
Boissier L, Hotz B, Proy C, Faugeras O, Fua P. Autonomous planetary rover (V.A.P.): On-board perception system concept and stereovision by correlation approach Proceedings - Ieee International Conference On Robotics and Automation. 1: 181-186. |
0.6 |
|
| 1992 |
Faugeras O, Mundy J, Ahuja N, Dyer C, Pentland A, Jain R, Ikeuchi K, Bowyer K. Why aspect graphs are not (yet) practical for computer vision Cvgip: Image Understanding. 55: 212-218. |
0.6 |
|
| 1991 |
Zhang Z, Faugeras OD. Determining motion from 3D line segment matches: a comparative study Image and Vision Computing. 9: 10-19. DOI: 10.1016/0262-8856(91)90043-O |
0.6 |
|
| 1990 |
Liu Y, Huang TS, Faugeras OD. Determination of Camera Location from 2-D to 3-D Line and Point Correspondences Ieee Transactions On Pattern Analysis and Machine Intelligence. 12: 28-37. DOI: 10.1109/34.41381 |
0.6 |
|
| 1990 |
Deriche R, Faugeras O. Tracking line segments Image and Vision Computing. 8: 261-270. DOI: 10.1016/0262-8856(90)80002-B |
0.6 |
|
| 1990 |
Faugeras OD, Bras-Mehlman EL, Boissonnat JD. Representing stereo data with the Delaunay triangulation Artificial Intelligence. 44: 41-87. DOI: 10.1016/0004-3702(90)90098-K |
0.6 |
|
| 1990 |
Faugeras OD, Maybank S. Motion from point matches: Multiplicity of solutions International Journal of Computer Vision. 4: 225-246. DOI: 10.1007/BF00054997 |
0.6 |
|
| 1989 |
Ayache N, Faugeras OD. Maintaining Representations of the Environment of a Mobile Robot Ieee Transactions On Robotics and Automation. 5: 804-819. DOI: 10.1109/70.88101 |
0.6 |
|
| 1989 |
Huang TS, Faugeras OD. Some Properties of the E Matrix in Two-View Motion Estimation Ieee Transactions On Pattern Analysis and Machine Intelligence. 11: 1310-1312. DOI: 10.1109/34.41368 |
0.6 |
|
| 1989 |
Mitiche A, Faugeras O, Aggarwal JK. Counting straight lines Computer Vision, Graphics and Image Processing. 47: 353-360. DOI: 10.1016/0734-189X(89)90117-5 |
0.6 |
|
| 1989 |
Vaillant R, Faugeras OD. Using occluding contours for recovering shape properties of objects . 26-32. |
0.6 |
|
| 1988 |
Liu Y, Huang TS, Faugeras OD. Determination of camera location from 2D to 3D line and point correspondences . 82-88. |
0.6 |
|
| 1988 |
Mitiche A, Faugeras O, Aggarwal J. Counting the line Proceedings - International Conference On Pattern Recognition. 693-695. |
0.6 |
|
| 1988 |
Le Bras-Mehlman E, Schmitt M, Faugeras OD, Boissonnat JD. How the Delaunay triangulation can be used for representing stereo data . 54-63. |
0.6 |
|
| 1987 |
Faugeras OD, Toscani G. CAMERA CALIBRATION FOR 3D COMPUTER VISION . 240-247. |
0.6 |
|
| 1987 |
Toscani G, Faugeras OD. STRUCTURE FROM MOTION USING THE RECONSTRUCTION AND REPROJECTION TECHNIQUE . 345-348. |
0.6 |
|
| 1987 |
Toscani G, Faugeras OD. STRUCTURE AND MOTION FROM TWO NOISY PERSPECTIVE VIEWS . 221-227. |
0.6 |
|
| 1986 |
Faugeras OD, Hebert M. REPRESENTATION, RECOGNITION, AND LOCATING OF 3-D OBJECTS International Journal of Robotics Research. 5: 27-52. DOI: 10.1177/027836498600500302 |
0.6 |
|
| 1986 |
Ayache N, Faugeras OD. HYPER: A New Approach for the Recognition and Positioning of Two—Dimensional Objects Ieee Transactions On Pattern Analysis and Machine Intelligence. 44-54. DOI: 10.1109/TPAMI.1986.4767751 |
0.6 |
|
| 1986 |
Faugeras OD, Lustman F. IDENTIFYING PLANES FOR THE CONSTRUCTION OF THE WORLD MODEL OF A MOBILE ROBOT Proceedings - International Conference On Pattern Recognition. 162-164. |
0.6 |
|
| 1986 |
Faugeras OD, Lustman F. INFERRING PLANES BY HYPOTHESIS PREDICTION AND TESTING FOR A MOBILE ROBOT . 211-223. |
0.6 |
|
| 1986 |
Faugeras OD, Hebert M. The representation, recognition, and positioning of 3-D shapes from range data Techniques For 3-D Machine Perception. 13-51. |
0.6 |
|
| 1986 |
Faugeras OD, Lustman F. LET US SUPPOSE THAT THE WORLD IS PIECEWISE PLANAR . 33-39. |
0.6 |
|
| 1986 |
Faugeras OD, Ayache N, Faverjon B. BUILDING VISUAL MAPS BY COMBINING NOISY STEREO MEASUREMENTS . 1433-1438. |
0.6 |
|
| 1986 |
Faugeras OD, Toscani G. CALIBRATION PROBLEM FOR STEREO . 15-20. |
0.6 |
|
| 1985 |
Ayache N, Faugeras O, Faverjon B. A Geometric Matcher for Recognizing and Positioning 3-D Rigid Objects Proceedings of Spie - the International Society For Optical Engineering. 521: 152-159. DOI: 10.1117/12.946175 |
0.6 |
|
| 1985 |
Faugeras OD. NEW STEPS TOWARD A FLEXIBLE 3-D VISION SYSTEM FOR ROBOTICS . 25-33. |
0.6 |
|
| 1984 |
Bhanu B, Faugeras OD. Shape Matching of Two-Dimensional Objects Ieee Transactions On Pattern Analysis and Machine Intelligence. 137-156. DOI: 10.1109/TPAMI.1984.4767499 |
0.6 |
|
| 1984 |
Ayache N, Faugeras OD. NEW METHOD FOR THE RECOGNITION AND POSITIONING OF 2-D OBJECTS Proceedings - International Conference On Pattern Recognition. 2: 1274-1277. |
0.6 |
|
| 1982 |
Bhanu B, Faugeras OD. Segmentation of Images Having Unimodal Distributions Ieee Transactions On Pattern Analysis and Machine Intelligence. 408-419. DOI: 10.1109/TPAMI.1982.4767273 |
0.6 |
|
| 1981 |
Faugeras OD, Price KE. Semantic description of aerial images using stochastic labeling Ieee Transactions On Pattern Analysis and Machine Intelligence. 6. DOI: 10.1109/TPAMI.1981.4767164 |
0.6 |
|
| Show low-probability matches. |
