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Designing geovisual analytics environments and displays with humans in mind / Arzu Çöltekin in ISPRS International journal of geo-information, vol 8 n° 12 (December 2019)
[article]
Titre : Designing geovisual analytics environments and displays with humans in mind Type de document : Article/Communication Auteurs : Arzu Çöltekin, Auteur ; Sidonie Christophe , Auteur ; Anthony Robinson, Auteur ; Urška Demšar, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Article en page(s) : n° 572 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle
[Termes IGN] interface homme-machine
[Termes IGN] langage naturel (informatique)
[Termes IGN] réalité virtuelle
[Termes IGN] représentation cartographique 3D
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) [Introduction] In this open-access Special Issue, we feature a set of publications under the theme “Human-Centered Geovisual Analytics and Visuospatial Display Design”. As the title suggests, the scope of this collection is on human-centered questions regarding visual analytics software environments; and the design of visuospatial displays within and beyond these environments. The essential building blocks of visual analytics (VA) are computers and humans [1]. Without computers (i.e., technology and quantitative methods such as those used in statistics and data science) VA simply would not exist. For decades now, it has been clear that computers are better than humans in processing large amounts of data, being capable of storing and quickly retrieving what is needed. Mechanisms such as parsing and filtering, automated pattern detection and machine learning, manual queries, and coordinated-view visualizations make visual analytics environments amazingly versatile and powerful [2]. The tools contained in VA environments assist us in spatial learning, discovery, and decision making [3,4]. It is important to remember that they can really only play an assistive role however, because tasks such as learning, interpreting patterns to make discoveries, and decision making are inherently qualitative. Often the goal is to make decisions based on observed patterns and anomalies. Such patterns and anomalies are much more likely to emerge (and if they are known to exist, they are better expressed) with visualizations than via numbers or tables alone [5]. Numéro de notice : A2019-614 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi8120572 Date de publication en ligne : 11/12/2019 En ligne : https://doi.org/10.3390/ijgi8120572 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95213
in ISPRS International journal of geo-information > vol 8 n° 12 (December 2019) . - n° 572[article](re)Considering Bertin in the age of big data and visual analytics / Alan M. MacEachren in Cartography and Geographic Information Science, vol 46 n° 2 (March 2019)
[article]
Titre : (re)Considering Bertin in the age of big data and visual analytics Type de document : Article/Communication Auteurs : Alan M. MacEachren, Auteur Année de publication : 2019 Article en page(s) : pp 101 - 118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle
[Termes IGN] données massives
[Termes IGN] sémiologie graphique
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) This paper highlights a selection of core ideas articulated by Bertin and leveraged by many researchers over time, with particular attention to how the ideas relate to developments in cartography, big data, and visual analytics. A primary contribution is a bibliometric analysis of the impact of Bertin’s Semiology of Graphics at its 50th anniversary. A briefer bibliometric assessment of Graphics and Graphic Information Processing impacts is also provided. The bibliometric analysis includes exploration of citations to Semiology of Graphics over the entire time span (in both English and French editions) as well as more focused analysis by topic and outlet since the advent of visual analytics as a research domain. Then, very recent research related to cartography, visual analytics, and big data is examined in detail to determine if and how Bertin’s ideas continue to be leveraged and extended for current data representation and analysis challenges. After outlining some limitations of the bibliometric analysis, discussion reflects on the current relevance of Bertin’s ideas, potential applications in visual analytics, and the need for a complement to Sémiologie Graphique focused on interactive visual interfaces to an increasingly diverse array of display forms. The paper concludes with thoughts on next steps. Numéro de notice : A2019-095 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1507758 Date de publication en ligne : 12/10/2018 En ligne : https://doi.org/10.1080/15230406.2018.1507758 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92351
in Cartography and Geographic Information Science > vol 46 n° 2 (March 2019) . - pp 101 - 118[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2019021 RAB Revue Centre de documentation En réserve L003 Disponible Challenging deep image descriptors for retrieval in heterogeneous iconographic collections / Dimitri Gominski (2019)
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/1909.08866v1Langues : 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 contenuRésumé : (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
Titre : Exploring multiplexing tools for co-visualization in crisis units Type de document : Article/Communication Auteurs : Christelle Pierkot , Auteur ; Sidonie Christophe , Auteur ; Jean-François Girres , Auteur Editeur : ISCRAM proceedings Année de publication : 2019 Projets : MapMuxing / Christophe, Sidonie Conférence : ISCRAM 2019, 16th International Conference on Information Systems for Crisis Response and Management 19/05/2019 22/05/2019 Valencia Espagne Open Access Proceedings Importance : pp 403 - 420 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse visuelle
[Termes IGN] Caraïbes
[Termes IGN] données hétérogènes
[Termes IGN] données localisées
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] gestion de crise
[Termes IGN] multiplexage
[Termes IGN] outil d'aide à la décision
[Termes IGN] planification
[Termes IGN] risque naturel
[Termes IGN] secours d'urgence
[Termes IGN] tsunami
[Termes IGN] visualisation de données
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Natural hazards can generate damages in large inhabited areas in a very short time period. Crisis managers must plan interventions very quickly to facilitate the arrival of the first emergency. In a crisis unit, experts visualize heterogeneous visual representations of spatio-temporal information, in order to facilitate decision-making, based on various types of screens, i.e. laptops, tablets, or wall screens. Visualizing all this information at the same time on the same interface would lead to cognitive overload. In this paper, we assume that it could be of interest to provide innovative co-visualization models and tools, to bring hazard, geospatial and climate information together, in a shared interface. We propose to explore spatial and temporal multiplexing tools within a dedicated geovisualization environment, in order to help expert decision-making. The proposition is implemented with the case study of a tsunami event in the Caribbean sea. Numéro de notice : C2019-039 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : http://idl.iscram.org/files/christellepierkot/2019/1871_ChristellePierkot_etal20 [...] Format de la ressource électronique : URL proceedings Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95357 Documents numériques
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Titre : Learning scene geometry for visual localization in challenging conditions Type de document : Article/Communication Auteurs : Nathan Piasco , Auteur ; Désiré Sidibé, Auteur ; Valérie Gouet-Brunet , Auteur ; Cédric Demonceaux, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : PLaTINUM / Gouet-Brunet, Valérie Conférence : ICRA 2019, International Conference on Robotics and Automation 20/05/2019 24/05/2019 Montréal Québec - Canada Proceedings IEEE Importance : pp 9094 - 9100 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse visuelle
[Termes IGN] appariement d'images
[Termes IGN] carte de profondeur
[Termes IGN] descripteur
[Termes IGN] géométrie de l'image
[Termes IGN] image RVB
[Termes IGN] localisation basée vision
[Termes IGN] précision de localisation
[Termes IGN] prise de vue nocturne
[Termes IGN] robotique
[Termes IGN] scène urbaine
[Termes IGN] variation diurne
[Termes IGN] variation saisonnière
[Termes IGN] vision par ordinateurRésumé : (auteur) We propose a new approach for outdoor large scale image based localization that can deal with challenging scenarios like cross-season, cross-weather, day/night and longterm localization. The key component of our method is a new learned global image descriptor, that can effectively benefit from scene geometry information during training. At test time, our system is capable of inferring the depth map related to the query image and use it to increase localization accuracy. We are able to increase recall@1 performances by 2.15% on cross-weather and long-term localization scenario and by 4.24% points on a challenging winter/summer localization sequence versus state-of-the-art methods. Our method can also use weakly annotated data to localize night images across a reference dataset of daytime images. Numéro de notice : C2019-002 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICRA.2019.8794221 Date de publication en ligne : 12/08/2019 En ligne : http://doi.org/10.1109/ICRA.2019.8794221 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93774 Documents numériques
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