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Semantic signatures for large-scale visual localization / Li Weng in Multimedia tools and applications, vol 80 n° 15 (June 2021)  

Public [article]  inMultimedia tools and applications > vol 80 n° 15 (June 2021) . - pp 22347 - 22372 Titre : Semantic signatures for large-scale visual localization Type de document : Article/Communication Auteurs : Li Weng , Auteur ; Valérie Gouet-Brunet , Auteur ; Bahman Soheilian , Auteur Année de publication : 2021 Projets : THINGS2D0 / Gouet-Brunet, Valérie Article en page(s) : pp 22347 - 22372 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement sémantique [Termes IGN] extraction de traits caractéristiques [Termes IGN] image numérique [Termes IGN] information sémantique [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] segmentation sémantique [Termes IGN] zone urbaine Résumé : (auteur) Visual localization is a useful alternative to standard localization techniques. It works by utilizing cameras. In a typical scenario, features are extracted from captured images and compared with geo-referenced databases. Location information is then inferred from the matching results. Conventional schemes mainly use low-level visual features. These approaches offer good accuracy but suffer from scalability issues. In order to assist localization in large urban areas, this work explores a different path by utilizing high-level semantic information. It is found that object information in a street view can facilitate localization. A novel descriptor scheme called “semantic signature” is proposed to summarize this information. A semantic signature consists of type and angle information of visible objects at a spatial location. Several metrics and protocols are proposed for signature comparison and retrieval. They illustrate different trade-offs between accuracy and complexity. Extensive simulation results confirm the potential of the proposed scheme in large-scale applications. This paper is an extended version of a conference paper in CBMI’18. A more efficient retrieval protocol is presented with additional experiment results. Numéro de notice : A2021-787 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers ArXiv Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11042-020-08992-6 Date de publication en ligne : 07/05/2020 En ligne : https://doi.org/10.1007/s11042-020-08992-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95407 [article]

Landmark based localization in urban environment / Xiaozhi Qu in ISPRS Journal of photogrammetry and remote sensing, vol 140 (June 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 140 (June 2018) . - pp 90 - 103 Titre : Landmark based localization in urban environment Type de document : Article/Communication Auteurs : Xiaozhi Qu , Auteur ; Bahman Soheilian , Auteur ; Nicolas Paparoditis , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Gouet-Brunet, Valérie Article en page(s) : pp 90 - 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] amer [Termes IGN] compensation locale par faisceaux [Termes IGN] données localisées 3D [Termes IGN] données multicapteurs [Termes IGN] estimation de pose [Termes IGN] incertitude géométrique [Termes IGN] odomètre [Termes IGN] précision décimétrique [Termes IGN] propagation d'incertitude Résumé : (auteur) A landmark based localization with uncertainty analysis based on cameras and geo-referenced landmarks is presented in this paper. The system is developed to adapt different camera configurations for six degree-of-freedom pose estimation. Local bundle adjustment is applied for optimization and the geo-referenced landmarks are integrated to reduce the drift. In particular, the uncertainty analysis is taken into account. On the one hand, we estimate the uncertainties of poses to predict the precision of localization. On the other hand, uncertainty propagation is considered for matching, tracking and landmark registering. The proposed method is evaluated on both KITTI benchmark and the data acquired by a mobile mapping system. In our experiments, decimeter level accuracy can be reached. Numéro de notice : A2018-198 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.09.010 Date de publication en ligne : 28/09/2017 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89867 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018061	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018063	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018062	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Semantic signatures for urban visual localization / Li Weng (2018)  

Public Titre : Semantic signatures for urban visual localization Type de document : Article/Communication Auteurs : Li Weng , Auteur ; Bahman Soheilian , Auteur ; Valérie Gouet-Brunet , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2018 Projets : 2-Pas d'info accessible - article non ouvert / Gouet-Brunet, Valérie Conférence : CBMI 2018, 16th International Conference on Content-Based Multimedia Indexing 04/09/2018 06/09/2018 La Rochelle France Proceedings IEEE Importance : 6 p. Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] base de données localisées [Termes IGN] extraction de traits caractéristiques [Termes IGN] information sémantique [Termes IGN] zone urbaine Résumé : (auteur) Visual localization is a useful alternative to standard localization techniques. In a typical scenario, features are extracted from images captured by cameras and compared with geo-referenced databases. Location information is then inferred from the matching results. Conventional schemes mainly use low-level visual features. They offer good accuracy but suffer from scalability issues. In order to assist localization in large urban areas, this work explores a different path by utilizing high-level semantic information. It is found that object information in a street view can facilitate localization. A novel descriptor scheme called “semantic signature” is proposed to summarize this information. A semantic signature consists of type and angle information of visible objects at a spatial location. Several metrics and protocols are proposed for signature comparison and retrieval. They illustrate different trade-offs between accuracy and complexity. Extensive simulation results confirm the potential of the proposed scheme in large-scale applications. Numéro de notice : C2018-064 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/CBMI.2018.8516492 Date de publication en ligne : 15/11/2018 En ligne : https://doi.org/10.1109/CBMI.2018.8516492 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91430

Effects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling / Yi Hong in Applied sciences, vol 7 n° 9 (September 2017)  

Public [article]  inApplied sciences > vol 7 n° 9 (September 2017) Titre : Effects of using different sources of remote sensing and geographic information system data on urban stormwater 2D–1D modeling Type de document : Article/Communication Auteurs : Yi Hong, Auteur ; Céline Bonhomme, Auteur ; Bahman Soheilian , Auteur ; Ghassan Chebbo, Auteur Année de publication : 2017 Projets : TrafiPollu / Gouet-Brunet, Valérie Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 2D [Termes IGN] données localisées 3D [Termes IGN] eau pluviale [Termes IGN] logiciel de simulation [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de terrain [Termes IGN] réseau d'assainissement [Termes IGN] ruissellement [Termes IGN] surface imperméable [Termes IGN] utilisation du sol [Termes IGN] ville [Termes IGN] zone urbaine Résumé : (auteur) Remote sensing (RS) and geographic information system (GIS) data is increasingly used in urban stormwater modeling. The undirected use of such data may waste economic and human resources. In order to provide guidance for practitioners to efficiently use different data collection resources, as well as give a reference for future works, this paper aims to assess the effects of using free access GIS data and ad hoc RS data on urban 2D–1D stormwater modeling. The 2D-surface Two-dimensional Runoff, Erosion, and Export model (TREX) model was published in Science of the Total Environment in 2008. The 1D-sewer CANOE (Logiciel intégré de conception et de diagnostic des réseaux d’assainissement) model was published in Journal of Hydrology in 2004. The two models are integrated in the TRENOE (TREX-CANOE) platform. The modeling approach is applied to a small urban catchment near Paris (Le Perreux sur Marne, 0.12 km2). Simulation results reveal that the detailed land-use information derived from multiple data sources is a crucial factor for accurate simulations. Nevertheless, using the very high resolution LiDAR (light detection and ranging) data is not equally significant for the water flow simulations at sewage outlets. Finally, we suggest that using the free access GIS data accompanying the urban sewer network design might be an acceptable low-cost solution for accurate urban 2D–1D stormwater modeling during moderate rainfall events. Further studies of urban stormwater modeling could focus on the development of “suitable” models with “enough” input data, depending on the management/research objectives. Numéro de notice : A2017-842 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/app7090904 Date de publication en ligne : 05/09/2017 En ligne : https://doi.org/10.3390/app7090904 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89409 [article]

Cross-domain image localization by adaptive feature fusion / Neelanjan Bhowmik (2017)  

Public Titre : Cross-domain image localization by adaptive feature fusion Type de document : Article/Communication Auteurs : Neelanjan Bhowmik , Auteur ; Li Weng , Auteur ; Valérie Gouet-Brunet , Auteur ; Bahman Soheilian , Auteur 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] similitude Résumé : (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

Quelle carte numérique pour le véhicule autonome ? / Pascal Vasseur in Transport environnement circulation TEC, n° 231 (novembre 2016)  

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Hybrid online mobile laser scanner calibration through image alignment by mutual information / Mourad Miled in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-1 (July 2016)  

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Evaluation of SIFT and SURF for vision based localization / Xiaozhi Qu (2016)    

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Landmark based localization: LBA refinement using MCMC-optimized projections of RJMCMC-extracted road marks / Bahman Soheilian (2016)  

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Localisation à base d’amers visuels : Cartographie et mise en correspondance de marquages au sol et intégration dans LBA / Bahman Soheilian (2016)    

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Uncertainty propagation for terrestrial mobile laser scanner / Miloud Mezian (2016)  

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Road marking extraction using a model&data-driven RJ-MCMC / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)    

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Augmenting vehicle localization accuracy with cameras and 3D road infrastructure database / Lijun Wei (2015)  

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Vehicle localization using mono-camera and geo-referenced traffic signs / Xiaozhi Qu (2015)  

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Combinatorial clustering and its application to 3D polygonal traffic sign reconstruction from multiple images / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)  

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