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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]

A GIS-based stochastic approach to generating daytime population distributions for vehicle route planning / K. Lau in Transactions in GIS, vol 13 n°5-6 (October/december 2009)  

Public [article]  inTransactions in GIS > vol 13 n°5-6 (October/december 2009) . - pp 481 - 502 Titre : A GIS-based stochastic approach to generating daytime population distributions for vehicle route planning Type de document : Article/Communication Auteurs : K. Lau, Auteur Année de publication : 2009 Article en page(s) : pp 481 - 502 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] itinéraire [Termes IGN] Melbourne [Termes IGN] milieu urbain [Termes IGN] modèle stochastique [Termes IGN] planification urbaine [Termes IGN] répartition géographique [Termes IGN] réseau routier [Termes IGN] surveillance routière [Termes IGN] transport routier Résumé : (Auteur) This article explores the use of daytime population distributions for vehicle route planning in urban environments when proximity to population is a major consideration. A GIS-based stochastic geocoding algorithm is proposed to generate daytime population distribution patterns using travel survey data. Metropolitan Melbourne in Australia is used as a test case with data collected from the Victorian Activity and Travel Survey between 1994 and 1999. The advantage of employing daytime population distributions for vehicle route planning is then illustrated taking dangerous goods delivery and mobile billboard advertising as examples. Analysis suggests that the proposed algorithm generates population distribution patterns with finer spatial and temporal details than that obtained using other estimation methods. The algorithm also eliminates the problem of over- or under-estimation of population associated with previous attempts using travel survey data and therefore provides more accurate results. Copyright Blackwell Publishing Numéro de notice : A2009-525 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2009.01175.x En ligne : https://doi.org/10.1111/j.1467-9671.2009.01175.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30154 [article]

Traffic extraction and characterisation from optical remote sensing data / Stefan Hinz in Photogrammetric record, vol 23 n° 124 (December 2008 - February 2009)  

Public [article]  inPhotogrammetric record > vol 23 n° 124 (December 2008 - February 2009) . - pp 424 - 440 Titre : Traffic extraction and characterisation from optical remote sensing data Type de document : Article/Communication Auteurs : Stefan Hinz, Auteur ; D. Lenhart, Auteur ; Jens Leitloff, Auteur Année de publication : 2008 Conférence : ISPRS 2007, High-Resolution Earth Imaging for Geospatial Information workshop 29/05/2007 01/06/2007 Hanovre Allemagne Article en page(s) : pp 424 - 440 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] base de données routières [Termes IGN] données multisources [Termes IGN] extraction de données [Termes IGN] image aérienne [Termes IGN] image optique [Termes IGN] image satellite [Termes IGN] modèle sémantique de données [Termes IGN] prise en compte du contexte [Termes IGN] surveillance routière [Termes IGN] trafic routier Résumé : (Auteur) This paper presents a generic scheme to extract traffic information from both optical satellite imagery and optical airborne image sequences. The extraction is based on an explicit semantic model of traffic, from which, depending on the characteristics of the input data, different strategies for vehicle detection, vehicle queue extraction and motion estimation are derived. The model comprises different scales to exploit the scale-dependent properties of traffic imaged by optical sensors. It is furthermore extended by context information to include knowledge about background objects as well as metadata from a road database in a consistent way. Various tests with different input data have been carried out and compared with manually acquired ground truth data of vehicles and vehicle tracks. The results show clearly the high potential of airborne and spaceborne traffic monitoring, but also indicate room for methodological improvements and exhibit some inherent sensor-related drawbacks. Copyright RS&PS + Blackwell Publishing Numéro de notice : A2008-421 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2008.00497.x En ligne : https://doi.org/10.1111/j.1477-9730.2008.00497.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29492 [article]