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Josiane Zerubia
Head of the team, INRIA
Keywords : Stochastic Geometry, Markov Random Fields, MCMC, Parameter Estimation, Deconvolution, Texture, Classification
Projects : Mode de Vie, Shapes, P2R France-Israel, ANR Diamond (PI)
Demos : see this author's demos
Contact :
| Mail : | | JosianedotZerubiaatinriadotfr | | Phone : | | (33)4-92-38-78-65 | | Fax : | | (33)4-92-38-76-43 | | Postal adress : | | INRIA Sophia Antipolis
2004, route des Lucioles
06902 Sophia Antipolis Cedex
France | | Webpage : | | visit ! |
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| Abstract :
Josiane Zerubia has been a permanent research scientist at INRIA since 1989, and director of research since July 1995. She was head of the PASTIS remote sensing laboratory (INRIA Sophia-Antipolis) from mid-1995 to 1997. Since January 1998, she has been head of the Ariana research group (INRIA/CNRS/University of Nice), which also works on remote sensing. She has been adjunct professor at SUPAERO (ISAE) in Toulouse since 1999. Before that, she was with the Signal and Image Processing Institute of the University of Southern California (USC) in Los-Angeles as a postdoc. She also worked as a researcher for the LASSY (University of Nice/CNRS) from 1984 to 1988 and in the Research Laboratory of Hewlett Packard in France and in Palo-Alto (CA) from 1982 to 1984. She received the MSc degree from the Department of Electrical Engineering at ENSIEG, Grenoble, France in 1981, and the Doctor of Engineering degree, her PhD, and her `Habilitation', in 1986, 1988, and 1994 respectively, all from the University of Nice Sophia-Antipolis, France.
She is a Fellow of the IEEE. She is a member of the IEEE IMDSP and IEEE BISP Technical Committees (SP Society). She was associate editor of IEEE Trans. on IP from 1998 to 2002; area editor of IEEE Trans. on IP from 2003 to 2006; guest co-editor of a special issue of IEEE Trans. on PAMI in 2003; and member-at-large of the Board of Governors of the IEEE SP Society from 2002 to 2004. She has also been a member of the editorial board of the French Society for Photogrammetry and Remote Sensing (SFPT) since 1998, of the International Journal of Computer Vision since 2004, and of the Foundation and Trends in Signal Processing since 2007. She has been associate editor of the on-line resource: Earthzine (IEEE CEO and GEOSS).
She was co-chair of two workshops on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01, Sophia Antipolis, France, and EMMCVPR'03, Lisbon, Portugal); co-chair of a workshop on Image Processing and Related Mathematical Fields (IPRM'02, Moscow, Russia); chair of a workshop on Photogrammetry and Remote Sensing for Urban Areas, Marne La Vallee, France, 2003; and co-chair of the special sessions at IEEE ICASSP 2006 (Toulouse, France) and of IEEE ISBI 2008 (Paris, France). She is a member of the organizing committee of IEEE ICIP 2014 (Paris, France).
Her current research interests are in image processing using probabilistic models and variational methods. She also works on parameter estimation and optimization techniques. |
Teaching :
- Cours sur les Modèles stochastiques en traitement d'image, Master STIC "Image et Géométrie pour le Multimédia et la Modélisation du Vivant"
- Cours 3ème année Sup'Aero (IS, module Filtrage et Segmentation en Imagerie Spatiale) |
Last publications in Ariana Research Group :
Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours. M. S. Kulikova and I. H. Jermyn and X. Descombes and E. Zhizhina and J. Zerubia. In IS&T/SPIE Electronic Imaging, San Jose, USA, January 2010. Keywords : Object extraction, Marked point process, shape prior, Active contour, birth-and-death dynamics. Copyright : Copyright 2010 by SPIE and IS&T. This paper was published in the proceedings of IS&T/SPIE Electronic Imaging 2010 Conference in San Jose, USA, and is made available as an electronic reprint with permission of SPIE and IS&T. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
@INPROCEEDINGS{Kulikova10a,
|
| author |
= |
{Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, |
| title |
= |
{Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours}, |
| year |
= |
{2010}, |
| month |
= |
{January}, |
| booktitle |
= |
{IS&T/SPIE Electronic Imaging}, |
| address |
= |
{San Jose, USA}, |
| keyword |
= |
{Object extraction, Marked point process, shape prior, Active contour, birth-and-death dynamics} |
| } |
Abstract :
We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. From an alternative point of view, the approach can be viewed as an extension of the active contour methodology to an a priori unknown number of
objects. Sampling and estimation are based on a stochastic birth-and-death process defined on the configuration space of an arbitrary number of objects, where the objects are defined by the image data and prior information. The performance of the approach is demonstrated via experimental results on synthetic and real data. |
High resolution SAR-image classification by Markov random fields and finite mixtures. G. Moser and V. Krylov and S. Serpico and J. Zerubia. In IS&T/SPIE Electronic Imaging, San Jose, USA, January 2010. Keywords : SAR image classification, Dictionary, amplitude probability density, Stochastic Expectation Maximization, Markov random field, copula. Copyright : SPIE and IS&T, 2010
@INPROCEEDINGS{moserSPIE2010a,
|
| author |
= |
{Moser, G. and Krylov, V. and Serpico, S. and Zerubia, J.}, |
| title |
= |
{High resolution SAR-image classification by Markov random fields and finite mixtures}, |
| year |
= |
{2010}, |
| month |
= |
{January}, |
| booktitle |
= |
{IS&T/SPIE Electronic Imaging}, |
| address |
= |
{San Jose, USA}, |
| url |
= |
{http://hal.archives-ouvertes.fr/inria-00442348/en/}, |
| pdf |
= |
{http://hal.archives-ouvertes.fr/docs/00/44/23/48/PDF/moserSPIE2010a.pdf}, |
| keyword |
= |
{SAR image classification, Dictionary, amplitude probability density, Stochastic Expectation Maximization, Markov random field, copula} |
| } |
Abstract :
In this paper we develop a novel classification approach for high and very high resolution polarimetric synthetic aperture radar (SAR) amplitude images. This approach combines the Markov random field model to Bayesian image classification and a finite mixture technique for probability density function estimation. The finite mixture modeling is done via a recently proposed dictionary-based stochastic expectation maximization approach for SAR amplitude probability density function estimation. For modeling the joint distribution from marginals corresponding to single polarimetric channels we employ copulas. The accuracy of the developed semiautomatic supervised algorithm is validated in the application of wet soil classification on several high resolution SAR images acquired by TerraSAR-X and COSMO-SkyMed. |
Structural approach for building reconstruction from a single DSM. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(1): pages 135-147, 2010.
@ARTICLE{lafarge_pami09,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Structural approach for building reconstruction from a single DSM}, |
| year |
= |
{2010}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| volume |
= |
{32}, |
| number |
= |
{1}, |
| pages |
= |
{135-147}, |
| url |
= |
{http://www2.computer.org/portal/web/csdl/doi/10.1109/TPAMI.2008.281}, |
| keyword |
= |
{} |
| } |
|
All publications in Ariana Research Group
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