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Maria Kulikova
Ancien Doctorant, University of Nice - Sophia-Antipolis - France
Mots-clés : Contours Actifs d'Ordre Supérieur, Contours actifs, MCMC, Segmentation, Classification, Extraction d'objets, Arbres / Foret, Super-résolution Projets : Mode de Vie, Shapes Démos : voir les démos de l'auteur
Contact :
E-Mail : | | MariadotSdotKulikovaatgmaildotcom | Téléphone : | | +33-(0)4-92-38-75-69 | Fax : | | +33-(0)4-92-38-76-43 | Adresse : | | INRIA Sophia Antipolis
2004, route des Lucioles
06902 Sophia Antipolis Cedex
France | Site personnel : | | visitez ! |
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| Résumé :
Les images de télédétection disponibles sur le marché civil sont de plus en plus résolues. Les résolutions des images satellitaires optiques actuelles atteignent quelques dizaines de centimètres. A ces résolutions, l’information n’est plus uniquement contenue au niveau du pixel et de son voisinage. En effet, la géométrie des objets devient accessible.
De nouveaux modèles stochastiques, définis dans le cadre des processus ponctuels marqués, ont récemment vu le jour en analyse d’image. Ils permettent de coupler les avantages de modèles plus classiques comme les champs de Markov à la prise en compte de l’information géométrique. Le principe est de définir une densité sur un espace de configurations constitué d’un ensemble d’objets géométriques simples (disques, rectangles, ...). Ils ont été appliqués dans le projet Ariana à l’extraction de différents items cartographiques tels que les routes, le bâti ou encore les arbres. L’objectif de nottre travail est de généraliser cette approche à des formes quelconques. |
Mini CV :
10.2006-12.2009 ► PhD au projet Ariana, INRIA Sophia-Antipolis, supervisé par I.Jermyn, X. descombes, and J.Zerubia
04.2006-09.2006 ► Stage du Master MVA au project Ariana, INRIA Sophia Antipolis
2005-2006 ► Ecole Normal Superieur de Cachan (ENS-Cachan). Master recherche en mathématiques appliquées, spécialité «Mathématiques Vision et Apprentissage».
1999-2005 ► Ecole d’Aéronautique de Moscou (MAI). Etudes d'ingénieur en mathématiques appliquées, spécialité « Equation différentielles et Modélisation mathématique en économie ». |
Enseignement :
01.2009-06.2009 ► TDs de Création et Manipulation de Documents (avec XHTML, XML, LaTeX, OOffice), 1er cycle, Polytech'Nice Sophia- Antipolis
01.2008-06.2008 ► TDs de Création et Manipulation de Documents (avec (X)HTML, XML, LaTeX, MSOffice), 1er cycle, Polytech'Nice Sophia- Antipolis
01.2007-06.2007 ► TDs de Jeu & Stratégie, 1er cycle, Polytech'Nice Sophia- Antipolis |
Dernières publications dans le projet Ariana :
A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images. M. S. Kulikova et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. International Journal of Computer Vision and Image Processing, 1(2): pages 1-12, 2011. Mots-clés : Contour actif, Processus ponctuels marques, multiple birth-and-death dynamics, multiple object extraction, Shape prior.
@ARTICLE{kulikova_ijcvip2010,
|
author |
= |
{Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, |
title |
= |
{A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images}, |
year |
= |
{2011}, |
journal |
= |
{International Journal of Computer Vision and Image Processing}, |
volume |
= |
{1}, |
number |
= |
{2}, |
pages |
= |
{1-12}, |
url |
= |
{http://hal.archives-ouvertes.fr/hal-00804118}, |
keyword |
= |
{Contour actif, Processus ponctuels marques, multiple birth-and-death dynamics, multiple object extraction, Shape prior} |
} |
Abstract :
Object extraction from images is one of the most important tasks in remote sensing image analysis. For accurate extraction from very high resolution (VHR) images, object geometry needs to be taken into account. A method for incorporating strong yet flexible prior shape information into a marked point process model for the extraction of multiple objects of complex shape is presented. To control the computational complexity, the objects considered are defined using the image data and the prior shape information. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process on the space of multiple objects. The authors present several experimental results on the extraction of tree crowns from VHR aerial images. |
Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours. M. S. Kulikova et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. Dans Proc. IS&T/SPIE Electronic Imaging, San Jose, USA, janvier 2010. Mots-clés : Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, 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 |
= |
{janvier}, |
booktitle |
= |
{Proc. IS&T/SPIE Electronic Imaging}, |
address |
= |
{San Jose, USA}, |
pdf |
= |
{http://hal.archives-ouvertes.fr/docs/00/46/54/72/PDF/Kulikova_SPIE2010.pdf}, |
keyword |
= |
{Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, 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. |
A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects. M. S. Kulikova et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. Dans Proc. IEEE SITIS, Publ. IEEE Computer Society, Marrakech, Maroc, décembre 2009. Mots-clés : Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, multiple birth-and-death dynamics.
@INPROCEEDINGS{Kulikova09a,
|
author |
= |
{Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, |
title |
= |
{A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects}, |
year |
= |
{2009}, |
month |
= |
{décembre}, |
booktitle |
= |
{Proc. IEEE SITIS}, |
publisher |
= |
{IEEE Computer Society}, |
address |
= |
{Marrakech, Maroc}, |
pdf |
= |
{http://hal.inria.fr/docs/00/43/63/20/PDF/PID1054029.pdf}, |
keyword |
= |
{Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, multiple birth-and-death dynamics} |
} |
Abstract :
We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple
objects. The single objects considered are defined by both the image data
and the prior information in a way that controls the computational
complexity of the estimation problem. The method is tested via experiments
on a very high resolution aerial image of a scene composed of tree crowns. |
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Liste complète des publications dans le projet Ariana
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