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POEME / Da Silva, Jean-Claude
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Nom :
POEME
titre complet :
Environnement immersif pour l'exploration de contenus photographiques
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Auteurs :
Da Silva, Jean-Claude
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contenu dans The 23rd international conference on MultiMedia Modeling, MMM 2017 / Laurent Amsaleg (2017)
Titre : Adaptive and optimal combination of local features for image retrieval Type de document : Article/Communication Auteurs : Neelanjan Bhowmik , Auteur ; Valérie Gouet-Brunet
Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2017 Autre Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Collection : Lecture notes in Computer Science, ISSN 0302-9743 Projets : POEME / Da Silva, Jean-Claude Conférence : MMM 2017, 23rd international conference on Multimedia Modeling 04/01/2017 06/01/2017 Reykjavik Islande Proceedings Springer Importance : pp 76 - 88 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] modèle de régression
[Termes IGN] point d'intérêt
[Termes IGN] recherche d'image basée sur le contenuRésumé : (Auteur) With the large number of local feature detectors and descriptors in the literature of Content-Based Image Retrieval (CBIR), in this work we propose a solution to predict the optimal combination of features, for improving image retrieval performances, based on the spatial complementarity of interest point detectors. We review several complementarity criteria of detectors and employ them in a regression based prediction model, designed to select the suitable detectors combination for a dataset. The proposal can improve retrieval performance even more by selecting optimal combination for each image (and not only globally for the dataset), as well as being profitable in the optimal fitting of some parameters. The proposal is appraised on three state-of-the-art datasets to validate its effectiveness and stability. The experimental results highlight the importance of spatial complementarity of the features to improve retrieval, and prove the advantage of using this model to optimally adapt detectors combination and some parameters. Numéro de notice : C2017-021 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-51814-5_7 Date de publication en ligne : 01/06/2017 En ligne : https://doi.org/10.1007/978-3-319-51814-5_7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88988 Documents numériques
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Adaptive and optimal combination - preprintAdobe Acrobat PDFCombination of image descriptors for the exploration of cultural photographic collections / Neelanjan Bhowmik in Journal of Electronic Imaging, vol 26 n° 1 (January - February 2017)
Titre : Combination of image descriptors for the exploration of cultural photographic collections Type de document : Article/Communication Auteurs : Neelanjan Bhowmik Année de publication : 2017 Projets : POEME / Da Silva, Jean-Claude Article en page(s) : pp 1 - 13 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données d'images
[Termes IGN] classification barycentrique
[Termes IGN] collection
[Termes IGN] fusion de données
[Termes IGN] image numérisée
[Termes IGN] moteur de recherche
[Termes IGN] patrimoine culturel
[Termes IGN] régression
[Termes IGN] web des donnéesRésumé : (Auteur) The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ. Numéro de notice : A2017-189 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1117/1.JEI.26.1.011019 Date de publication en ligne : 19/12/2016 En ligne : http://dx.doi.org/10.1117/1.JEI.26.1.011019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84799
in Journal of Electronic Imaging > vol 26 n° 1 (January - February 2017) . - pp 1 - 13[article]
Titre : Cross-domain image localization by adaptive feature fusion Type de document : Article/Communication Auteurs : Neelanjan Bhowmik Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2017 Projets : POEME / Da Silva, Jean-Claude Conférence : JURSE 2017, Joint urban remote sensing event 06/03/2017 08/03/2017 Lausanne Suisse Proceedings IEEE Importance : 4 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] environnement de développement
[Termes IGN] estimation de pose
[Termes IGN] géopositionnement
[Termes IGN] modèle de régression
[Termes IGN] recherche d'image basée sur le contenu
[Termes IGN] recherche d'information géographique
[Termes IGN] similitudeRésumé : (auteur) We address the problem of cross-domain image localization, i.e., the ability of estimating the pose of a landmark from visual content acquired under various conditions, such as old photographs, paintings, photos taken at a particular season, etc. We explore a 2D approach where the pose is estimated from geo-localized reference images that visually match the query image. This work focuses on the retrieval of similar images, which is a challenging task for images across different domains. We propose a Content-Based Image Retrieval (CBIR) framework that adaptively combines multiple image descriptions. A regression model is used to select the best feature combinations according to their spatial complementarity, globally for a whole dataset as well as adaptively for each given image. The framework is evaluated on different datasets and the experiments prove its advantage over classical retrieval approaches. Numéro de notice : C2017-028 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2017.7924572 Date de publication en ligne : 11/05/2017 En ligne : https://doi.org/10.1109/JURSE.2017.7924572 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89292
Titre : Efficient fusion of multidimensional descriptors for image retrieval Type de document : Article/Communication Auteurs : Neelanjan Bhowmik Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Projets : POEME / Da Silva, Jean-Claude Conférence : ICIP 2014, 21st IEEE International Conference on Image Processing 27/10/2014 30/10/2014 Paris France Proceedings IEEE Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse visuelle
[Termes IGN] banque d'images
[Termes IGN] base de données d'images
[Termes IGN] descripteur
[Termes IGN] état de l'art
[Termes IGN] fusion de données
[Termes IGN] index
[Termes IGN] mesure de similitude
[Termes IGN] recherche d'image basée sur le contenu
[Termes IGN] réductionRésumé : (auteur) Due to the large diversity of existing feature descriptors in content-based image retrieval, the image contents can be better represented by the joint use of several descriptors in order to explore their potentially complementary characteristics. This paper presents and discusses a strategy for fusion of the different multidimensional features involved, based on inverted multi-indices and dedicated to similarity search. Image descriptors are quantized separately and efficiently through dimension reduction techniques, before being combined in the inverted multi-indices. To exhibit its effectiveness, the proposal is evaluated on two datasets having different contents and sizes, facing several state-of-the-art approaches of image descriptor fusion. The obtained results reconfirm that the joint use of several descriptions improves similarity search, and show that our fusion proposal outperforms other solutions, while manipulating lower or similar volumes of features. Numéro de notice : C2014-033 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2014.7026166 Date de publication en ligne : 29/01/2015 En ligne : https://doi.org/10.1109/ICIP.2014.7026166 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92058 Documents numériques
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Efficient fusion of multidimensional ... - pdf auteurAdobe Acrobat PDF
