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Detection and 3D reconstruction of traffic signs from multiple view color images / Bahman Soheilian in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 77 (March 2013) . - pp 1 - 20 Titre : Detection and 3D reconstruction of traffic signs from multiple view color images Type de document : Article/Communication Auteurs : Bahman Soheilian , Auteur ; Nicolas Paparoditis , Auteur ; Bruno Vallet , Auteur Année de publication : 2013 Projets : CityVIP / Paparoditis, Nicolas Article en page(s) : pp 1 - 20 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement automatique [Termes IGN] couleur (variable spectrale) [Termes IGN] figure géométrique [Termes IGN] géométrie épipolaire [Termes IGN] programmation par contraintes [Termes IGN] Ransac (algorithme) [Termes IGN] reconstruction 3D [Termes IGN] segmentation d'image [Termes IGN] signalisation routière Résumé : (Auteur) 3D reconstruction of traffic signs is of great interest in many applications such as image-based localization and navigation. In order to reflect the reality, the reconstruction process should meet both accuracy and precision. In order to reach such a valid reconstruction from calibrated multi-view images, accurate and precise extraction of signs in every individual view is a must. This paper presents first an automatic pipeline for identifying and extracting the silhouette of signs in every individual image. Then, a multi-view constrained 3D reconstruction algorithm provides an optimum 3D silhouette for the detected signs. The first step called detection, tackles with a color-based segmentation to generate ROIs (Region of Interests) in image. The shape of every ROI is estimated by fitting an ellipse, a quadrilateral or a triangle to edge points. A ROI is rejected if none of the three shapes can be fitted sufficiently precisely. Thanks to the estimated shape the remained candidates ROIs are rectified to remove the perspective distortion and then matched with a set of reference signs using textural information. Poor matches are rejected and the types of remained ones are identified. The output of the detection algorithm is a set of identified road signs whose silhouette in image plane is represented by and ellipse, a quadrilateral or a triangle. The 3D reconstruction process is based on a hypothesis generation and verification. Hypotheses are generated by a stereo matching approach taking into account epipolar geometry and also the similarity of the categories. The hypotheses that are plausibly correspond to the same 3D road sign are identified and grouped during this process. Finally, all the hypotheses of the same group are merged to generate a unique 3D road sign by a multi-view algorithm integrating a priori knowledges about 3D shape of road signs as constraints. The algorithm is assessed on real and synthetic images and reached and average accuracy of 3.5cm for position and 4.5° for orientation. Numéro de notice : A2013-111 Affiliation des auteurs : IGN (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.11.009 date de publication en ligne : 26/01/2013 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.11.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32249 [article]

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Generation of an integrated 3D city model with visual landmarks for autonomous navigation in dense urban areas / Bahman Soheilian (June 2013)    

Public Titre : Generation of an integrated 3D city model with visual landmarks for autonomous navigation in dense urban areas Type de document : Article/Communication Auteurs : Bahman Soheilian , Auteur ; Olivier Tournaire, Auteur ; Nicolas Paparoditis , Auteur ; Bruno Vallet , Auteur ; Jean-Pierre Papelard , Auteur Congrès : IV 2013, IEEE Intelligent Vehicles Symposium (23 - 26 juin 2013; Gold Coast City, Australie) , Commanditaire Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : June 2013 Projets : CityVIP / Paparoditis, Nicolas Importance : pp 304 - 309 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données localisées [Termes IGN] bati [Termes IGN] données localisées 3D [Termes IGN] navigation autonome [Termes IGN] route [Termes IGN] vision par ordinateur Résumé : (auteur) In the context of urban autonomous navigation systems for going from point A to point B, a practicable trajectory which takes into account drivable areas and permanent obstacles should be designed first. A robot should then follow this trajectory while avoiding not only dynamic obstacles such as cars and pedestrians but also permanent obstacles such as road sides and central islands. To this end, a robot must be aware of its exact position and must be informed of what its immediate environment is at all times. In dense urban areas, GNSS systems generally suffer from lack of precision due to masks and multipaths. Localization systems have to model these phenomena and even merge with vision based methods in order to obtain the high accuracies required in the process. In this paper, we propose an integrated geographic database enabling, on the one hand, the GNSS and vision based localization methods to obtain the required accuracy, and on the other, to provide the robots with information about its surroundings such as drivable surfaces and permanent obstacles. The database is comprised of 3D buildings, 3D roads and a set of 3D visual landmarks. Our system provides most of the information required for autonomous navigation in dense urban areas and has successfully been embedded in real experiments, thanks to a real-time querying system. Numéro de notice : C2013-041 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : INFORMATIQUE/POSITIONNEMENT Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IVS.2013.6629486 date de publication en ligne : 15/10/2013 En ligne : https://doi.org/10.1109/IVS.2013.6629486 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80148

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