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scientifique

Learning embeddings for cross-time geographic areas represented as graphs / Margarita Khokhlova (2021)  

Public Titre : Learning embeddings for cross-time geographic areas represented as graphs Type de document : Article/Communication Auteurs : Margarita Khokhlova, Auteur ; Nathalie Abadie , Auteur ; Valérie Gouet-Brunet , Auteur ; Liming Chen, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SAC 2021, 36th Annual ACM Symposium on Applied Computing 22/03/2021 26/03/2021 en ligne Proceedings ACM Importance : pp 559 - 568 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] arête [Termes IGN] classification par réseau neuronal [Termes IGN] entité géographique [Termes IGN] graphe flou [Termes IGN] image aérienne à axe vertical [Termes IGN] noeud [Termes IGN] relation spatiale [Termes IGN] représentation graphique [Termes IGN] réseau neuronal de graphes Résumé : (auteur) Geographic entities from the vertical aerial images can be viewed as discrete objects and represented as nodes in a graph, linked to each other by edges capturing their spatial relationships. Over time, the natural and man made landscape may evolve and thus also their graph representations. This paper addresses the challenging problem of the retrieval and fuzzy matching of graphs to localize near-identical geographical areas across time. Several use-case scenarios are proposed for the end-to-end learning of a graph embedding using Graph Neural Networks (GNN), along with an effective baseline without learning. The results demonstrate the efficiency of our approach, that enables efficient similarity reasoning for novel hand-engineered cross-time graph data. Code and data processing scripts are available online. Numéro de notice : C2021-002 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3412841.3441936 En ligne : https://doi.org/10.1145/3412841.3441936 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97583

How to spatialize geographical iconographic heritage / Emile Blettery (2021)    

Public contenu dans SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2021)   Titre : How to spatialize geographical iconographic heritage Type de document : Article/Communication Auteurs : Emile Blettery , Auteur ; Nelson Fernandes, Auteur ; Valérie Gouet-Brunet , Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SUMAC 2021, 3rd workshop on Structuring and Understanding of Multimedia heritAge Contents 20/10/2021 24/10/2021 Chengdu Chine Proceedings ACM Importance : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données d'images [Termes IGN] estimation de pose [Termes IGN] géolocalisation [Termes IGN] géoréférencement indirect [Termes IGN] image ancienne [Termes IGN] image numérisée [Termes IGN] patrimoine culturel [Termes IGN] photographie aérienne oblique [Termes IGN] photographie terrestre [Termes IGN] recherche d'image basée sur le contenu Résumé : (auteur) This article is dedicated to the spatialization of image contents, with a focus on geographical iconographic heritage, i.e. digitized or born-digital image collections, acquired at variable temporal periods and showing the territory and its human-made and natural visual landmarks. We present a panorama of the current solutions (manual, semi-automatic and fully automatic alternatives) that exist to spatialize a visual content, with respect to the data available and the level of spatialization targeted. In particular, we highlight the characteristics of the approaches dedicated to geographical iconographic heritage, and in some cases, we present tests and practical feedbacks that we had the opportunity to conduct for old photographic contents in oblique aerial and terrestrial imagery. Numéro de notice : C2021-035 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3475720.3484444 En ligne : https://doi.org/10.1145/3475720.3484444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99054

Documents numériques

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SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2021)  

Public Titre : SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents Type de document : Actes de congrès Auteurs : Valérie Gouet-Brunet , Éditeur scientifique ; Margarita Khokhlova, Éditeur scientifique ; Ronak Kosti, Éditeur scientifique ; Li Weng , Éditeur scientifique Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2021 Conférence : SUMAC 2021, 3rd workshop on Structuring and Understanding of Multimedia heritAge Contents 20/10/2021 24/10/2021 Chengdu Chine Proceedings ACM Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] exploration d'images [Termes IGN] image numérique [Termes IGN] image numérisée [Termes IGN] patrimoine culturel [Termes IGN] recherche d'image basée sur le contenu Numéro de notice : 13912 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : 10.1145/3475720 En ligne : https://doi.org/10.1145/3475720 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99053

Contient

• How to spatialize geographical iconographic heritage / Emile Blettery (2021)    

SUMAC'20 : Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2020)  

Public Titre : SUMAC'20 : Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents Type de document : Actes de congrès Auteurs : Valérie Gouet-Brunet , Auteur ; Margarita Khokhlova, Auteur ; Ronak Kosti, Auteur ; Liming Chen, Auteur ; Xu-Chen Yin, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2020 Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SUMAC 2020, 2nd workshop on Structuring and Understanding of Multimedia heritAge Contents 12/10/2020 12/10/2020 en ligne Etats-Unis Proceedings ACM ISBN/ISSN/EAN : 978-1-4503-8155-0 Langues : Anglais (eng) Descripteur : [Termes IGN] conservation du patrimoine [Termes IGN] descripteur [Termes IGN] données massives [Termes IGN] multimedia [Termes IGN] numérisation de photographie [Termes IGN] recherche d'image basée sur le contenu Résumé : (auteur) It is our great pleasure to welcome you to SUMAC 2020, the 2nd edition of the ACM workshop on Structuring and Understanding of Multimedia heritAge Contents. The digitization of large quantities of analogue data and the massive production of born-digital documents for many years now provide us with large volumes of varied multimedia data (images, maps, text, video, multi-sensor data, etc.), an important feature of which is that they are cross-domain. "Cross-domain" reflects the fact that these data may have been acquired in very different conditions: different acquisition systems, times and points of view (e.g. a 1962 postcard from the Arc de Triomphe vs. a recent street-view acquisition by mobile mapping of the same monument). These data represent an extremely rich heritage that can be exploited in a wide variety of fields, from SSH to land use and territorial policies, including smart city, urban planning, tourism, creative media and entertainment. In terms of research in computer science, they address challenging problems related to the diversity and volume of the media across time, the variety of content descriptors (potentially including the time dimension), the veracity of the data, and the different user needs with respect to engaging with this rich material and the extraction of value out of the data. These challenges are reflected in research topics such as multimodal and mixed media search, automatic content analysis, multimedia linking and recommendation, and big data analysis and visualization, where scientific bottlenecks may be exacerbated by the time dimension, which also provides topics of interest such as multimodal time series analysis. Numéro de notice : 17631 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : 10.1145/3423323 En ligne : https://dl.acm.org/doi/proceedings/10.1145/3423323 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97086

Challenging deep image descriptors for retrieval in heterogeneous iconographic collections / Dimitri Gominski (2019)  

Public Titre : Challenging deep image descriptors for retrieval in heterogeneous iconographic collections Type de document : Article/Communication Auteurs : Dimitri Gominski , Auteur ; Martyna Poreba , Auteur ; Valérie Gouet-Brunet , Auteur ; Liming Chen, Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2019 Autre Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Projets : Alegoria / Gouet-Brunet, Valérie Conférence : SUMAC 2019, 1st workshop on Structuring and Understanding of Multimedia heritAge Contents 21/10/2019 21/10/2019 Nice France Proceedings ACM Importance : pp 31 - 38 Format : 21 x 30 cm Note générale : bibliographie Preprint publié sur ArXiv https://arxiv.org/abs/1909.08866v1 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse visuelle [Termes IGN] apprentissage profond [Termes IGN] base de données d'images [Termes IGN] collection [Termes IGN] descripteur [Termes IGN] données hétérogènes [Termes IGN] exploration de données [Termes IGN] extraction de traits caractéristiques [Termes IGN] iconographie [Termes IGN] image multi sources [Termes IGN] indexation [Termes IGN] jeu de données [Termes IGN] recherche d'image basée sur le contenu Résumé : (auteur) This article proposes to study the behavior of recent and efficient state-of-the-art deep-learning based image descriptors for content-based image retrieval, facing a panel of complex variations appearing in heterogeneous image datasets, in particular in cultural collections that may involve multi-source, multi-date and multi-view contents. For this purpose, we introduce a novel dataset, namely Alegoria dataset, consisting of 12,952 iconographic contents representing landscapes of the French territory, and encapsultating a large range of intra-class variations of appearance which were finely labelled. Six deep features (DELF, NetVLAD, GeM, MAC, RMAC, SPoC) and a hand-crafted local descriptor (ORB) are evaluated against these variations. Their performance are discussed, with the objective of providing the reader with research directions for improving image description techniques dedicated to complex heterogeneous datasets that are now increasingly present in topical applications targeting heritage valorization. Numéro de notice : C2019-022 Affiliation des auteurs : LASTIG MATIS (2012-2019) Autre URL associée : ArXiv Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3347317.3357246 Date de publication en ligne : 19/09/2019 En ligne : https://doi.org/10.1145/3347317.3357246 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93623

Voir aussi

• SUMAC 2019, 1st workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2019)  

SUMAC 2019, 1st workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2019)  

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Assessing the planimetric accuracy of Paris atlases from the late 18th and 19th centuries / Bertrand Duménieu (2018)    

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An adaptive approach for interlinking georeferenced data / Abdelfettah Feliachi (2017)  

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Continuously generalizing buildings to built-up areas by aggregating and growing / Dongliang Peng (2017)  

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Evaluation of NER systems for the recognition of place mentions in French thematic corpora / Carmen Brando (2016)  

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Progressive streaming and massive rendering of 3D city models on web-based virtual globe / Quoc-Dinh Nguyen (2016)  

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Realtime projective multi-texturing of pointclouds and meshes for a realistic street-view web navigation / Alexandre Devaux (2016)    

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A multi-layer markup language for geospatial semantic annotations / Ludovic Moncla (2015)  

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Proceedings of the 9th Workshop on Geographic Information Retrieval, GIR'2015 / Ross S. Purves (2015)  

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TEXTOMAP : determining geographical window for texts / Geoffrey Brun (2015)  

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