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Publications sur multiple object extraction
Résultat de la recherche dans la liste des publications :
Article |
1 - 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. |
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Thèse de Doctorat et Habilitation |
1 - Shape recognition for image scene analysis.
M. S. Kulikova. Thèse de Doctorat, Universite de Nice - Sophia-Antipolis, décembre 2009.
Mots-clés : tree crown , Classification, Forme, multiple object extraction, Processus ponctuels marques, Shape prior.
@PHDTHESIS{mkulikova_phd09,
|
| author |
= |
{Kulikova, M. S.}, |
| title |
= |
{Shape recognition for image scene analysis}, |
| year |
= |
{2009}, |
| month |
= |
{décembre}, |
| school |
= |
{Universite de Nice - Sophia-Antipolis}, |
| url |
= |
{http://tel.archives-ouvertes.fr/docs/00/48/20/19/PDF/phd_mkulikova_2009.pdf}, |
| keyword |
= |
{tree crown , Classification, Forme, multiple object extraction, Processus ponctuels marques, Shape prior} |
| } |
Résumé :
Cette thèse est composée de deux parties principales. La première partie est dédiée au problème de la classification d’espèces d’arbres en utilisant des descripteurs de forme, en combainison ou non, avec ceux de radiométrie ou de texture. Nous montrons notamment que l’information sur la forme améliore la performance d’un classifieur. Pour ce faire, dans un premier temps, une étude des formes de couronnes d’arbres extraites à partir d’images aériennes, en infrarouge couleur, est e ectuée en utilisant une méthodologie d’analyse de
formes des courbes continues fermées dans un espace de formes, en utilisant la notion de chemin géodésique sous deux métriques dans des espaces appropriés : une métrique non-élastique en utilisant la reprèsentation par la fonction d’angle de la courbe, ainsi qu’une métrique élastique induite par une représentation par la racinecarée appelée q-fonction. Une étape préliminaire nécessaire à la classification est l’extraction des couronnes d’arbre. Dans une seconde partie, nous abordons donc le problème de l’extraction d’objets de forme complexe
arbitraire, à partir d’images de télédétection à très haute résolution. Nous construisons un modèle fondé sur les processus ponctuels marqués. Son originalité tient dans sa prise en compte d’objets de forme arbitraire par rapport aux objets de forme paramétrique, e.g. ellipses ou rectangles. Les formes sélectionnées sont obtenues par la minimisation locale d’une énergie de type contours actifs avec di érents a priori sur la forme incorporé. Les objets de la configuration finale (optimale) sont ensuite sélectionnés parmi les candidats par une dynamique
de naissances et morts multiples, couplée à un schéma de recuit simulé. L’approche est validée sur des images de zones forestières à très haute résolution fournies par l’Université d’Agriculture de Suède. |
Abstract :
This thesis includes two main parts. In the first part we address the problem of tree crown classification into species using shape features, without, or in combination with, those of radiometry and texture, to demonstrate that shape information improves classification performance. For this purpose, we first study the shapes of tree crowns extracted from very high resolution colour aerial infra-red images. For our study, we choose a methodology based on the shape analysis of closed continuous curves on shape spaces using geodesic paths under the bending metric with the angle-function curve representation, and the elastic metric with the square root
q-function representation. A necessary preliminary step to classification is extraction of the tree crowns. In the second part, we address thus the problem of extraction of multiple objects with complex, arbitrary shape from remote sensing images of very high resolution. We develop a model based on marked point processes. Its originality lies in its use of arbitrarily-shaped objects as opposed to parametric shape objects, e.g. ellipses or rectangles. The shapes considered are obtained by local minimisation of an active contour energy with weak and then strong shape prior knowledge included. The objects in the final (optimal) configuration are then selected from amongst these candidates by a multiple birth-and-death dynamics embedded in an annealing scheme. The approach is validated on very high resolution images of forest provided by the Swedish University of Agriculture. |
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2 Articles de conférence |
1 - A fast multiple birth and cut algorithm using belief propagation.
A. Gamal Eldin et X. Descombes et Charpiat G. et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, septembre 2011.
Mots-clés : Multiple Birth and Cut, multiple object extraction, Graph Cut, Belief Propagation.
@INPROCEEDINGS{MBC_ICIP11,
|
| author |
= |
{Gamal Eldin, A. and Descombes, X. and G., Charpiat and Zerubia, J.}, |
| title |
= |
{A fast multiple birth and cut algorithm using belief propagation}, |
| year |
= |
{2011}, |
| month |
= |
{septembre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Brussels, Belgium}, |
| url |
= |
{http://hal.inria.fr/inria-00592446/fr/}, |
| keyword |
= |
{Multiple Birth and Cut, multiple object extraction, Graph Cut, Belief Propagation} |
| } |
Abstract :
In this paper, we present a faster version of the newly proposed Multiple Birth and Cut (MBC) algorithm. MBC is an optimization method applied to the energy minimization of an object based model, defined by a marked point process. We show that, by proposing good candidates in the birth step of this algorithm, the speed of convergence is increased. The algorithm starts by generating a dense configuration in a special organization, the best candidates are selected using the belief propagation algorithm. Next, this candidate configuration is combined with the current configuration using binary graph cuts as presented in the original version of the MBC algorithm. We tested the performance of our algorithm on the particular problem of counting flamingos in a colony, and show that it is much faster with the modified birth step. |
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2 - A novel algorithm for occlusions and perspective effects using a 3d object process.
A. Gamal Eldin et X. Descombes et J. Zerubia. Dans ICASSP 2011 (International Conference on Acoustics, Speech and Signal Processing), Prague, Czech Republic, mai 2011.
Mots-clés : Occlusions, 3D object process, multiple object extraction, Multiple Birth and Death, Penguins Counting.
@INPROCEEDINGS{ICASSP_2011,
|
| author |
= |
{Gamal Eldin, A. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A novel algorithm for occlusions and perspective effects using a 3d object process}, |
| year |
= |
{2011}, |
| month |
= |
{mai}, |
| booktitle |
= |
{ICASSP 2011 (International Conference on Acoustics, Speech and Signal Processing)}, |
| address |
= |
{Prague, Czech Republic}, |
| url |
= |
{http://hal.inria.fr/inria-00592449/fr/}, |
| keyword |
= |
{Occlusions, 3D object process, multiple object extraction, Multiple Birth and Death, Penguins Counting} |
| } |
Abstract :
In this paper, we introduce a novel probabilistic approach to handle occlusions and perspective effects. The proposed method is an object based method embedded in a marked point process framework. We apply it for the size estimation of a penguin colony, where we model a penguin colony as an unknown number of 3D objects. The main idea of the proposed approach is to sample some candidate configurations consisting of 3D objects lying in the real plane. A Gibbs energy is define on the configuration space, which takes into account both prior and data information. These configurations are projected onto the image plane. The configurations are modified until convergence using the multiple birth and death optimization algorithm and by measuring the similarity between the projected image of the configuration and the real image. During optimization, the proposed configuration is modeled by a mixed graph which represents all dependencies between the objects, including interaction between neighbor objects and parent-child dependency for occluded objects. We tested our model on synthetic image, and real images. |
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