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Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data / Siavash Hosseinyalamdary in ISPRS International journal of geo-information, vol 4 n°3 (September 2015)  

Public [article]  inISPRS International journal of geo-information > vol 4 n°3 (September 2015) . - pp 1301 - 1316 Titre : Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data Type de document : Article/Communication Auteurs : Siavash Hosseinyalamdary, Auteur ; Yashar Balazadegan, Auteur ; Charles K. Toth, Auteur Année de publication : 2015 Article en page(s) : pp 1301 - 1316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] détection d'objet [Termes IGN] données localisées 3D [Termes IGN] filtre de Kalman [Termes IGN] objet géographique 3D [Termes IGN] objet mobile [Termes IGN] poursuite de cible [Termes IGN] semis de points [Termes IGN] surveillance routière [Termes IGN] trafic routier Résumé : (auteur) Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS) map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM), can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR) data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS) and Inertial Measurement Unit (IMU) navigation solution. Numéro de notice : A2015-711 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi4031301 En ligne : https://doi.org/10.3390/ijgi4031301 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78348 [article]