pr\u00e9sentent<\/p>\n\n\n\n
Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Institut Polytechnique de Paris, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en :<\/p>\n\n\n\n
le MARDI 12 D\u00c9CEMBRE 2023 \u00e0 10h00<\/p>\n\n\n\n
\u00e0
T\u00e9l\u00e9com SudParis
C06
9 rue Charles Fourier 91011 EVRY<\/p>\n\n\n\n
Membres du jury :<\/strong><\/p>\n\n\n\n M. Titus ZAHARIA<\/strong>, Professeur, T\u00e9l\u00e9com SudParis, FRANCE – Directeur de these R\u00e9sum\u00e9 :<\/strong><\/p>\n\n\n\n Ce projet doctoral se focalise sur les probl\u00e9matiques associ\u00e9es \u00e0 l’identification d’images et de documents dans les applications de r\u00e9alit\u00e9 augment\u00e9e utilisant des marqueurs, en particulier lors de l’utilisation d’appareils photo. La recherche s’inscrit dans un contexte technologique o\u00f9 l’interaction via la r\u00e9alit\u00e9 augment\u00e9e est essentielle dans plusieurs domaines, y compris l’industrie, qui requi\u00e8rent des m\u00e9thodologies d’identification fiables. Dans une premi\u00e8re phase, le projet \u00e9value diverses m\u00e9thodologies d’identification et de traitement d’image au moyen d’une base de donn\u00e9es sp\u00e9cialement con\u00e7ue pour refl\u00e9ter les d\u00e9fis du contexte industriel. Cette recherche permet une analyse approfondie des m\u00e9thodologies existantes, r\u00e9v\u00e9lant ainsi leurs potentiels et leurs limites dans divers sc\u00e9narios d’application. Par la suite, le projet propose un syst\u00e8me de d\u00e9tection de documents visant \u00e0 am\u00e9liorer les solutions existantes, optimis\u00e9 pour des environnements tels que les navigateurs web. Ensuite, une m\u00e9thodologie innovante pour la recherche d’images est introduite, s’appuyant sur une analyse de l’image en sous-parties afin d’accro\u00eetre la pr\u00e9cision de l’identification et d’\u00e9viter les confusions d’images. Cette approche permet une identification plus pr\u00e9cise et adaptative, notamment en ce qui concerne les variations de la mise en page de l’image cible. Enfin, dans le cadre de travaux en collaboration avec la soci\u00e9t\u00e9 ARGO, un moteur de suivi d’image en temps r\u00e9el a \u00e9t\u00e9 d\u00e9velopp\u00e9, optimis\u00e9 pour des appareils \u00e0 basse puissance et pour les environnements web. Ceci assure le d\u00e9ploiement d’applications web en r\u00e9alit\u00e9 augment\u00e9e et leur fonctionnement sur un large \u00e9ventail de dispositifs, y compris ceux dot\u00e9s de capacit\u00e9s de traitement limit\u00e9es. Il est \u00e0 noter que les travaux issus de ce projet doctoral ont \u00e9t\u00e9 appliqu\u00e9s et valoris\u00e9s concr\u00e8tement par la soci\u00e9t\u00e9 Argo \u00e0 des fins commerciales, confirmant ainsi la pertinence et la viabilit\u00e9 des m\u00e9thodologies et solutions d\u00e9velopp\u00e9es, et attestant de leur contribution significative au domaine technologique et industriel de la r\u00e9alit\u00e9 augment\u00e9e.<\/p>\n\n\n\n Abstract :<\/strong><\/p>\n\n\n\n This doctoral project focuses on issues related to the identification of images and documents in augmented reality applications using markers, particularly when using cameras. The research is set in a technological context where interaction through augmented reality is essential in several domains, including industry, which require reliable identification methodologies. In an initial phase, the project assesses various identification and image processing methodologies using a database specially designed to reflect the challenges of the industrial context. This research allows an in-depth analysis of existing methodologies, thus revealing their potentials and limitations in various application scenarios. Subsequently, the project proposes a document detection system aimed at enhancing existing solutions, optimized for environments such as web browsers. Then, an innovative image research methodology is introduced, relying on an analysis of the image in sub-parts to increase the accuracy of identification and avoid image confusions. This approach allows for more precise and adaptive identification, particularly with respect to variations in the layout of the target image. Finally, in the context of collaborative work with ARGO company, a real-time image tracking engine was developed, optimized for low-power devices and web environments. This ensures the deployment of augmented reality web applications and their operation on a wide range of devices, including those with limited processing capabilities. It is noteworthy that the works resulting from this doctoral project have been concretely applied and valorized by the Argo company for commercial purposes, thereby confirming the relevance and viability of the developed methodologies and solutions, and attesting to their significant contribution to the technological and industrial field of augmented reality.<\/p>\n","protected":false},"excerpt":{"rendered":" L’Ecole doctorale : Ecole Doctorale de l’Institut Polytechnique de Paris et le Laboratoire de recherche SAMOVAR – Services r\u00e9partis, Architectures, Mod\u00e9lisation, Validation, Administration des R\u00e9seaux pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Monsieur Thibault LELONG Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Institut Polytechnique de Paris, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en : 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M. Marius PREDA<\/strong>, Ma\u00eetre de conf\u00e9rences, T\u00e9l\u00e9com SudParis, FRANCE – Co-encadrant de these
M. Christophe GRAVIER<\/strong>, Professeur, T\u00e9l\u00e9com Saint-Etienne, FRANCE – Rapporteur
M. Valeriu VRABIE<\/strong>, Professeur, Universit\u00e9 de Reims Champagne-Ardenne, FRANCE – Rapporteur
M. Mihai CIUC<\/strong>, Professeur, Polytechnic University of Bucharest, ROUMANIE – Examinateur
M. Emmanuel BRICARD<\/strong>, Ing\u00e9nieur, Shift89, Sparkles3, FRANCE – Examinateur<\/p>\n\n\n\n\u00ab Reconnaissance des documents avec de l’apprentissage profond pour la r\u00e9alit\u00e9 augment\u00e9e \u00bb<\/h2>\n\n\n\n
pr\u00e9sent\u00e9 par Monsieur Thibault LELONG<\/h2>\n\n\n\n