Emmanuel PRADOS

I am a scientist researcher at INRIA.
I lead the STEEP research group at the INRIA Grenoble - Rhone-Alpes Research Center.
This new research group tries to model regional transition to sustainability. Between 2006 and 2010, I worked in the Perception group (INRIA Rhone-Alpes). I was a postdoctoral researcher with Stefano Soatto at UCLA (2005). I graduated as a Ph.D. (2004) working with Professor Olivier Faugeras in the Odyssee Lab. (laboratory of Computer and Biological Vision of the INRIA/ENS/ENPC) at the INRIA of Sophia Antipolis
My competences involve various topics of applied mathematics and computer science:
theoretical analysis of Partial Differential Equations (PDEs),
numerical resolution and analysis of Partial Differential Equations,
control theory, differential games, dynamic programming,
variational methods and optimization,...
My research activities now focus on the application of mathematics and the computer science to the modelling of the transition to sustainability at local scale.
I am member of the group SOCLE3 [http: // socle3.inrialpes.fr/].
Previously, I was applying my skills to computer vision, in particular to the questions of:
3D scene reconstruction from monocular or multiview images / video sequences,
illumination, reflectance modeling and image formation,
image invariants, characterization of ambiguities,
segmentation, image matching, scene flow...
Award: Accessit of the SPECIF Prize in 2005 (Prize of the Best French PhD Thesis in Computer Science).
Contact
- INRIA Rhône-Alpes
655, avenue de l'Europe
38330 Montbonnot, France - Tel: +33 4 7661 52 27
- Fax: +33 4 7661 54 54
Links
Students
Projects
Research Topics
Recent publications[All publications]
Minimizing the Reprojection Error in Surface Reconstruction from Images
Proceedings of the International Conference on Computer Vision, Rio de Janeiro, Brazil - 2007
3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination
International Journal of Computer Vision, Volume 76, Number 3 - March 2008
Shape from Shading: a well-posed problem ?
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'05), San Diego, California, Volume II, Pages 870--877 - jun 2005
Control Theory and Fast Marching Techniques for Brain Connectivity Mapping
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, New York, NY, June, 2006, Volume 1, Pages 1076--1083 - June 2006
Fast Marching Method for Generic Shape From Shading
Proceedings of VLSM'05 (third International Workshop on Variational, Geometric and Level Set Methods in Computer Vision), Volume 3752, Pages 320–-331 - oct 2005
A unifying and rigorous Shape From Shading method adapted to realistic data and applications
Journal of Mathematical Imaging and Vision, Volume 25, Number 3, Pages 307--328 - 2006
A viscosity solution method for Shape-From-Shading without image boundary data
Mathematical Modelling and Numerical Analysis (M2AN), Volume 40, Number 2, Pages 393--412 - 2006
A generic and provably convergent Shape-From-Shading Method for Orthographic and Pinhole Cameras
International Journal of Computer Vision, Volume 65, Number 1/2, Pages 97--125 - nov 2005
Shape From Shading
Handbook of Mathematical Models in Computer Vision, Springer, Pages 375--388 - 2006
Perspective shape from shading and viscosity solutions
Proceedings of the 9th International Conference on Computer Vision, Volume 2, Pages 826--831 - oct 2003
Shape-from-Shading with discontinuous image brightness
Applied Numerical Mathematics, Volume 56, Number 9, Pages 1225--1237 - sept 2006
Unifying Approaches and Removing Unrealistic Assumptions in Shape from Shading: Mathematics Can Help
Proceedings of the 8th European Conference on Computer Vision, Prague, Czech Republic, Volume 3024, Pages 141--154 - 2004
Application of the theory of the viscosity solutions to the Shape From Shading problem
PhD Thesis from University of Nice-Sophia Antipolis, France - oct 2004



