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enviroCar: A citizen science platform for analyzing and mapping crowd-sourced car sensor data / Arne Bröring in Transactions in GIS, vol 19 n° 3 (June 2015)
[article]
Titre : enviroCar: A citizen science platform for analyzing and mapping crowd-sourced car sensor data Type de document : Article/Communication Auteurs : Arne Bröring, Auteur ; Albert Remke, Auteur ; Christophe Stasch, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 362 – 376 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] acquisition de données
[Termes IGN] capteur terrestre
[Termes IGN] diagnostic
[Termes IGN] données localisées des bénévoles
[Termes IGN] interface web
[Termes IGN] milieu urbain
[Termes IGN] réseau de capteurs
[Termes IGN] trafic routier
[Termes IGN] véhicule automobileRésumé : (auteur) This article presents the enviroCar platform for collecting geographic data acquired from automobile sensors and openly providing those data for further processing and analysis. By plugging a low-cost On-Board Diagnostics (OBD-II) adapter into a car and using an Android smartphone, various kinds of sensor data measured by today's cars can be collected and uploaded on to the Web. Once available on the Web, these data can be used to monitor traffic and related environmental parameters. We analyse the OBD-II interface and its potential usage for environmental monitoring, e.g. to estimate fuel consumption and resulting inline image emissions, noise emission, and standing times. Next, we present the main contribution of this article, the system design of the enviroCar platform. This system design consists of the enviroCar app and the enviroCar server, which allows for flexible geoprocessing of the uploaded data. We focus in this article on the description of the spatiotemporal RESTful Web Service interface and underlying data model specifically designed for handling the mobile sensor data. Finally, we present application scenarios in which the enviroCar platform can act as a powerful tool, e.g. regarding traffic monitoring and smarter cities (e.g. the detection of pollutant emission hotspots in the city), or towards applications for a quantified self (e.g. monitoring fuel consumption). We started the enviroCar project in 2013 and have been able to attract a growing number of participants since then. In a crowd-funding initiative, enviroCar was successfully funded by volunteers, demonstrating the interest in this platform. Numéro de notice : A2015-678 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12155 En ligne : http://dx.doi.org/10.1111/tgis.12155 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78304
in Transactions in GIS > vol 19 n° 3 (June 2015) . - pp 362 – 376[article]Augmenting vehicle localization accuracy with cameras and 3D road infrastructure database / Lijun Wei (2015)
Titre : Augmenting vehicle localization accuracy with cameras and 3D road infrastructure database Type de document : Article/Communication Auteurs : Lijun Wei , Auteur ; Bahman Soheilian , Auteur ; Valérie Gouet-Brunet , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2015 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 8925 Conférence : ECCV 2014, 13th European conference on computer vision, workshops 06/09/2014 12/09/2014 Zurich Suisse Proceedings Springer Importance : pp 194 - 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] base de données routières
[Termes IGN] données localisées 3D
[Termes IGN] précision de localisation
[Termes IGN] signalisation routière
[Termes IGN] véhicule automobileRésumé : (auteur) Accurate and continuous vehicle localization in urban environments has been an important research problem in recent years. In this paper, we propose a landmark based localization method using road signs and road markings. The principle is to associate the online detections from onboard cameras with the landmarks in a pre-generated road infrastructure database, then to adjust the raw vehicle pose predicted by the inertial sensors. This method was evaluated with data sequences acquired in urban streets. The results prove the contribution of road signs and road markings for reducing the trajectory drift as absolute control points. Numéro de notice : C2014-016 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : GEOMATIQUE/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-319-16178-5_13 Date de publication en ligne : 19/03/2015 En ligne : http://dx.doi.org/10.1007/978-3-319-16178-5_13 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83180
Titre : Change detection from mobile laser scanning point clouds Titre original : Détection de changements à partir de nuages de points de cartographie mobile Type de document : Thèse/HDR Auteurs : Wen Xiao, Auteur ; Nicolas Paparoditis , Directeur de thèse ; Bruno Vallet , Encadrant Editeur : Champs/Marne : Université Paris-Est Marne-la-Vallée UPEM Année de publication : 2015 Importance : 110 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de doctorat présentée pour obtenir le grade de docteur Université Paris-Est, Ecole Doctorale MSTIC, spécialité Sciences et Technologies de l’Information GéographiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage dirigé
[Termes IGN] détection d'objet
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] instrumentation Riegl
[Termes IGN] objet mobile
[Termes IGN] semis de points
[Termes IGN] véhicule automobileMots-clés libres : occupancy-based method Index. décimale : THESE Thèses et HDR Résumé : (auteur) Mobile mapping systems are increasingly used for street environment mapping, especially mobile laser scanning technology enables precise street mapping, scene understanding, facade modelling, etc. In this research, the change detection from laser scanning point clouds is investigated. First of all, street environment change detection using RIEGL data is studied for the purpose of database updating and temporary object identification. An occupancy-based method is presented to overcome the challenges encountered by the conventional distance-based method, such as occlusion, anisotropic sampling. Occluded areas are identified by modelling the occupancy states within the laser scanning range. The gaps between points and scan lines are interpolated under the sensor reference framework, where the sampling density is isotropic. Even there are some conflicts on penetrable objects, e.g. trees, fences, the occupancy-based method is able to enhance the point-to-triangle distance-based method. The change detection method is also applied to data acquired by different laser scanners at different temporal-scales with the intention to have wider range of applications. The local sensor reference framework is adapted to Velodyne laser scanning geometry. The occupancy-based method is implemented to detection moving objects. Since the method detects the change of each point, moving objects are detect at point level. As the Velodyne scanner constantly scans the surroundings, the trajectories of moving objects can be detected. A simultaneous detection and tracking algorithm is proposed to recover the pedestrian trajectories in order to accurately estimate the traffic flow of pedestrian in public places. Changes can be detected not only at point level, but also at object level. The changes of cars parking on street sides at different times are detected to help regulate on-street car parking since the parking duration is limited. In this case, cars are detected in the first place, then they are compared with corresponding ones. Apart from car changes, parking positions and car types are also important information for parking management. All the processes are solved in a supervised learning framework. Furthermore, a model-based car reconstruction method is proposed to precisely locate cars. The model parameters are also treated as car features for better decision making. Moreover, the geometrically accurate models can be used for visualization purposes. Under the theme of change detection, related topics, e.g. tracking, classification, modelling, are also studied for the reason of practical applications. More importantly, the change detection methods are applied to different data acquisition geometries at multiple temporal-scales. Both bottom-up (point-based) and top-down (object-based) change detection strategies are investigated. Note de contenu : 1 Introduction
1.1 Motivation
1.1.1 Fine-scale change detection
1.1.2 Applications
1.2 Problems
1.3 Mobile mapping system and data
1.3.1 REIGL laser scanner
1.3.2 Velodyne laser scanner
1.4 Objectives
1.5 Structure
1.6 Contribution
2 State-of-the-art
2.1 Change detection methods
2.2 Change detection from imageries
2.3 Change detection from airborne lidar data
2.4 Change detection from terrestrial lidar data
2.5 Change detection in related domains
3 Street Environment Change Detection
3.1 Introduction
3.2 Contribution
3.3 Occupancy-based change detection
3.3.1 Laser Scanning Geometry
3.3.2 Occupancy modelling for an individual ray
3.3.3 Occupancy fusion and corresponding point retrieval
3.3.4 Consistency assessment between different epochs
3.4 Combination with distance-based change detection
3.5 Experiments and result
3.6 Evaluation and discussion
3.7 Conclusion
4 Simultaneous detection and tracking of pedestrian
4.1 Introduction
4.2 Related work
4.2.1 Pedestrian tracking in computer vision
4.2.2 Pedestrian tracking using laser scanning data
4.3 Methodology
4.3.1 Moving object detection
4.3.2 Simultaneous detection and tracking of pedestrian
4.3.3 Optimization
4.4 Experiments and results
4.4.1 Moving object detection
4.4.2 Pedestrian tracking
4.5 Discussions
4.6 Conclusion
5 Street-side car detection, classification and change detection
5.1 Introduction
5.2 Related work
5.2.1 Vehicle detection
5.2.2 Vehicle modelling
5.3 Methodology
5.3.1 Segmentation and feature extraction
5.3.2 Car modelling
5.3.3 Car recognition and localization
5.3.4 Car classification
5.3.5 Change detection
5.4 Experiments and results
5.4.1 Segmentation
5.4.2 Car modelling
5.4.3 Car recognition
5.4.4 Car classification
5.4.5 Change detection
5.5 Conclusion
6 Conclusion and perspectives
6.1 Summary
6.2 Conclusion
6.3 PerspectivesNuméro de notice : 17339 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de doctorat : Sciences et Technologies de l’Information Géographique : Paris-Est : 2015 Organisme de stage : MATIS (IGN) nature-HAL : Thèse DOI : sans En ligne : https://theses.hal.science/tel-01373359 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83191
Titre : Vehicle localization using mono-camera and geo-referenced traffic signs Type de document : Article/Communication Auteurs : Xiaozhi Qu , Auteur ; Bahman Soheilian , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2015 Conférence : IV 2015, IEEE Intelligent Vehicles Symposium 28/06/2015 01/07/2015 Seoul Corée du Sud Proceedings Springer Importance : pp 605 - 610 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] base de données localisées
[Termes IGN] compensation locale par faisceaux
[Termes IGN] détection automatique
[Termes IGN] géopositionnement
[Termes IGN] image terrestre
[Termes IGN] point de repère
[Termes IGN] programmation par contraintes
[Termes IGN] signalisation routière
[Termes IGN] véhicule automobileRésumé : (auteur) Vision based localization is a cost effective method for indoor and outdoor application. However, it has drift problem if none global optimization is used. We proposed a geo-referenced traffic sign based localization method, which integrated the constraints of 3D traffic signs with local bundle adjustment to reduce the drift. Comparing to global bundle adjustment, Local Bundle Adjustment(LBA) has low computational cost but suffers the drift problem for large scale localization because of the random error accumulation. We reduced the drift by means of the constraints from geo-referenced traffic signs for bundle adjustment process. The original LBA model was extended for the constraints and the traffic signs were detected in images and matched with 3D landmark database automatically. From the experiments of simulated and real images, our approach can reduce the drift and have better locating results than none-constraint LBA based localization method. Numéro de notice : C2015-042 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/POSITIONNEMENT Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IVS.2015.7225751 Date de publication en ligne : 27/08/2015 En ligne : http://dx.doi.org/10.1109/IVS.2015.7225751 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83303 Detecting cars in UAV images with a catalog-based approach / Thomas Moranduzzo in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
[article]
Titre : Detecting cars in UAV images with a catalog-based approach Type de document : Article/Communication Auteurs : Thomas Moranduzzo, Auteur ; F. Melgani, Auteur Année de publication : 2014 Article en page(s) : pp 6356 - 6367 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] catalogue
[Termes IGN] détection d'objet
[Termes IGN] extraction automatique
[Termes IGN] histogramme
[Termes IGN] séparateur à vaste marge
[Termes IGN] traitement automatique de données
[Termes IGN] véhicule automobileRésumé : (Auteur) This paper presents a new method for the automatic detection of cars in unmanned aerial vehicle (UAV) images acquired over urban contexts. UAV images are characterized by an extremely high spatial resolution, which makes the detection of cars particularly challenging. The proposed method starts with a screening operation in which the asphalted areas are identified in order to make the car detection process faster and more robust. Subsequently, filtering operations in the horizontal and vertical directions are performed to extract histogram-of-gradient features and to yield a preliminary detection of cars after the computation of a similarity measure with a catalog of cars used as reference. Three different strategies for computing the similarity are investigated. Successively, for the image points identified as potential cars, an orientation value is computed by searching for the highest similarity value in 36 possible directions. The last step is devoted to the merging of the points which belong to the same car because it is likely that a car is identified by more than one point due to the extremely high resolution of UAV images. As outcomes, the proposed method provides the number of cars in the image, as well as the position and orientation for each of them. Interesting experimental results, conducted on a set of real UAV images acquired over an urban area, are presented and discussed. Numéro de notice : A2014-484 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2296351 En ligne : https://doi.org/10.1109/TGRS.2013.2296351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74067
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6356 - 6367[article]Réservation
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