Publications sur Multiple Birth and Cut

Résultat de la recherche dans la liste des publications :

• 1 Article
• 1 Thèse de Doctorat et Habilitation
• 2 Articles de conférence

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Article

1 - Multiple Birth and Cut Algorithm for Multiple Object Detection. A. Gamal Eldin et X. Descombes et Charpiat G. et J. Zerubia. Journal of Multimedia Processing and Technologies, 2011. Mots-clés : Markov point process, Multiple Birth and Cut, Graph Cut, Belief Propagation, flamingo counting. @ARTICLE{MBC_BP10, author = {Gamal Eldin, A. and Descombes, X. and G., Charpiat and Zerubia, J.}, title = {Multiple Birth and Cut Algorithm for Multiple Object Detection}, year = {2011}, journal = {Journal of Multimedia Processing and Technologies}, url = {http://hal.inria.fr/hal-00616371}, keyword = {Markov point process, Multiple Birth and Cut, Graph Cut, Belief Propagation, flamingo counting} } Abstract : In this paper, we describe a new optimization method which we call Multiple Birth and Cut (MBC). It combines the recently developed Multiple Birth and Death (MBD) algorithm and the Graph-Cut algorithm. MBD and MBC optimization methods are applied to energy minimization of an object based model, the marked point process. We compare the MBC to the MBD showing their respective advantages and drawbacks, where the most important advantage of the MBC is the reduction of number of parameters. We demonstrate that by proposing good candidates throughout the selection phase in the birth step, the speed of convergence is increased. In this selection phase, the best candidates are chosen from object sets by a belief propagation algorithm. We validate our algorithm on the flamingo counting problem in a colony and demonstrate that our algorithm outperforms the MBD algorithm.

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Thèse de Doctorat et Habilitation

1 - Processus ponctuels et algorithmes de coupure minimal de graphe appliqués à l'extraction d'objets 2D et 3D. A. Gamal Eldin. Thèse de Doctorat, Universite de Nice Sophia Antipolis, octobre 2011. Mots-clés : Multiple object detection, Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Marked point process, Stochastic geometry. @PHDTHESIS{GamalPhdThesis, author = {Gamal Eldin, A.}, title = {Processus ponctuels et algorithmes de coupure minimal de graphe appliqués à l'extraction d'objets 2D et 3D}, year = {2011}, month = {octobre}, school = {Universite de Nice Sophia Antipolis}, url = {http://tel.archives-ouvertes.fr/tel-00737988}, keyword = {Multiple object detection, Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Marked point process, Stochastic geometry} } Résumé : L'objectif de cette thèse est de développer une nouvelle approche de détection d'objets 3D à partir d'une image 2D, prenant en compte les occultations et les phénomènes de perspective. Cette approche est fondée sur la théorie des processus ponctuels marqués, qui a fait ses preuves dans la solution de plusieurs problèmes en imagerie haute résolution. Le travail de la thèse est structuré en deux parties: En première partie: Nous proposons une nouvelle méthode probabiliste pour gérer les occultations et les effets de perspective. Le modèle propose est fondé sur la simulation d'une scène 3D utilisant OpenGL sur une carte graphique (GPU). C'est une méthode orientée objet, intégrée dans le cadre d'un processus ponctuel marqué. Nous l'appliquons pour l'estimation de la taille d'une colonie de manchots, là où nous modélisons une colonie de manchots comme un nombre inconnu d'objets 3D. L'idée principale de l'approche proposée consiste à échantillonner certaines configurations candidat composé d'objets 3D s'appuyant sur le plan réel. Une densité de Gibbs est définie sur l'espace des configurations, qui prend en compte des informations a priori et sur les données. Pour une configuration proposée, la scène est projetée sur le plan image, et les configurations sont modifiées jusqu'à convergence. Pour évaluer une configuration proposée, nous mesurons la similarité entre l'image projetée de la configuration proposée et l'image réelle, définissant ainsi le terme d'attache aux données et l'a priori pénalisant les recouvrements entre objets. Nous avons introduit des modifications dans l'algorithme d'optimisation pour prendre en compte les nouvelles dépendances qui existent dans notre modèle 3D. En deuxième partie: Nous proposons une nouvelle méthode d'optimisation appelée Abstract : The topic of this thesis is to develop a novel approach for 3D object detection from a 2D image. This approach takes into consideration the occlusions and the perspective effects. This work has been embedded in a marked point process framework, proved to be efficient for solving many challenging problems dealing with high resolution images. The accomplished work during the thesis can be presented in two parts: First part: We propose a novel probabilistic approach to handle occlusions and perspective effects. The proposed method is based on 3D scene simulation on the GPU using OpenGL. It 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 on the real plane. A Gibbs energy is define on the configuration space, which takes into account both prior and data information. The proposed configurations are projected onto the image plane, and the configurations are modified until convergence. To evaluate a proposed configuration, we measure the similarity between the projected image of the proposed configuration and the real image, by defining a data term and a prior term which penalize objects overlapping. We introduced modifications to the optimization algorithm to take into account new dependencies that exists in our 3D model. Second part: We propose a new optimization method which we call

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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.

2 - Multiple Birth and Cut Algorithm for Point Process Optimization. A. Gamal Eldin et X. Descombes et J. Zerubia. Dans Proc. IEEE International Conference on Signal-Image Technology and Internet-based Systems (SITIS), Kuala Lumpur, Malaysia, décembre 2010. Mots-clés : Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Processus ponctuels marques. @INPROCEEDINGS{MBC_MPP_SITIS10, author = {Gamal Eldin, A. and Descombes, X. and Zerubia, J.}, title = {Multiple Birth and Cut Algorithm for Point Process Optimization}, year = {2010}, month = {décembre}, booktitle = {Proc. IEEE International Conference on Signal-Image Technology and Internet-based Systems (SITIS)}, address = {Kuala Lumpur, Malaysia}, url = {http://hal.archives-ouvertes.fr/inria-00516305/fr/}, keyword = {Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Processus ponctuels marques} } Abstract : In this paper, we describe a new optimization method which we call Multiple Birth and Cut (MBC). It combines the recently developed Multiple Birth and Death (MBD) algorithm and the Graph-Cut algorithm. MBD and MBC optimization methods are applied to the energy minimization of an object based model, the marked point process. We compare the MBC to the MBD showing the advantages and disadvantages, where the most important advantage is the reduction of the number of parameters. We validated our algorithm on the counting problem of flamingos in colony, where our algorithm outperforms the performance of the MBD algorithm.

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