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Changing mobility patterns in the Netherlands during COVID-19 outbreak / Sander Van Der Drift in Journal of location-based services, vol 16 n° 1 (March 2022)  

Public [article]  inJournal of location-based services > vol 16 n° 1 (March 2022) . - pp 1 - 24 Titre : Changing mobility patterns in the Netherlands during COVID-19 outbreak Type de document : Article/Communication Auteurs : Sander Van Der Drift, Auteur ; Luc Wismans, Auteur ; Marie-José Olde-Kalter, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] bicyclette [Termes IGN] comportement [Termes IGN] épidémie [Termes IGN] estimation bayesienne [Termes IGN] mobilité territoriale [Termes IGN] Pays-Bas [Termes IGN] téléphone intelligent [Termes IGN] transport [Termes IGN] transport public [Termes IGN] travail à domicile [Termes IGN] véhicule automobile Résumé : (auteur) The COVID-19 outbreak and associated measures taken had an enormous impact on society as well as a disruptive, but not necessarily negative, impact on mobility. The Ministry of Infrastructure and Water Management received the most recent insights from the Dutch Mobility Panel (DMP) on a weekly basis. These insights were used to monitor the travel behaviour and to analyse changes in the behaviour of different groups and usage of modes of transport during COVID-19. The analysis shows an enormous decrease in travel at the beginning of the implementation of the so-called ‘intelligent’ lockdown and gradual increase again towards comparable levels as before this ‘intelligent lockdown, although the distribution over time, motives and used modes has changed. It becomes clear that not everyone needs to travel during peak hours and commuter travel is also not the main reason for the increase in car usage. Furthermore, cycling has shown to be an alternative option for travellers and public transport is hardly used anymore. If it is possible to sustain the lower level of car usage and integrate public transport as an important alternative for travel again, the COVID-19 impact on mobility could have a substantial remaining positive impact on mobility. Numéro de notice : A2022-391 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17489725.2021.1876259 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.1080/17489725.2021.1876259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100682 [article]

GIS-based employment availabilities by mode of transport in Kuwait / S. Alkheder in Applied geomatics, vol 14 n° 1 (March 2022)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 1 - 15 Titre : GIS-based employment availabilities by mode of transport in Kuwait Type de document : Article/Communication Auteurs : S. Alkheder, Auteur ; Waleed Abdullah, Auteur ; Hussain Al Sayegh, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 15 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse spatiale [Termes IGN] données socio-économiques [Termes IGN] établissement d'enseignement [Termes IGN] Koweit [Termes IGN] logement [Termes IGN] réseau de transport [Termes IGN] système d'information géographique [Termes IGN] trafic routier [Termes IGN] transport public [Termes IGN] travail [Termes IGN] véhicule automobile Résumé : (auteur) Public transit (PT) has a positive impact on social and environment development in any society. This paper was carried out to analyze the role of GIS in utilizing destination identification as a way to help accomplish a sustainable landscape. The work focused on enhancing work availability considering the transport network. Areas with a higher offer of zero-vehicle lodging units have a better employment availability by travel. Furthermore, areas with a higher offer of single-parent families are at a disadvantage in general occupation openness. In this paper, GIS-based employment availabilities by walking, transit, and automobile were processed for the metropolitan territory. The same was done for work availability among neighboring square gatherings, while regulating built-environment and socio-economic variables. Understanding public travel openness is imperative for encouraging mode movements to reduce auto dependence and is fundamental for the prosperity of non-car households. Also, it is important to know the distribution of facilities such as schools, universities, malls, and other socio-economic places, which helps in rearranging these places in a better way to have effective transit and to reduce road traffic. The accessibility analysis is done through three steps: identifying the spatial distribution in the area, creating buffers around each alternative, and calculating the total number of population and services served by the network. The overall results of this study show that the proposed network will cover more than 50% of school places and workplaces in the area. It will also serve about 840,000 inhabitants, which is 34% of the total population. The previous results make the network accessible to a large number of the area’s residents and will connect them with the main attraction points in the city. Numéro de notice : A2022-215 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-021-00406-y Date de publication en ligne : 18/10/2021 En ligne : https://doi.org/10.1007/s12518-021-00406-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100085 [article]

Deep learning based 2D and 3D object detection and tracking on monocular video in the context of autonomous vehicles / Zhujun Xu (2022)  

Public Titre : Deep learning based 2D and 3D object detection and tracking on monocular video in the context of autonomous vehicles Type de document : Thèse/HDR Auteurs : Zhujun Xu, Auteur ; Eric Chaumette, Directeur de thèse ; Damien Vivet, Directeur de thèse Editeur : Toulouse : Université de Toulouse Année de publication : 2022 Importance : 136 p. Format : 21 x 30 cm Note générale : bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, spécialité Informatique et Télécommunications Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] apprentissage semi-dirigé [Termes IGN] architecture de réseau [Termes IGN] détection d'objet [Termes IGN] échantillonnage de données [Termes IGN] objet 3D [Termes IGN] segmentation d'image [Termes IGN] véhicule automobile [Termes IGN] vidéo [Termes IGN] vision par ordinateur Résumé : (auteur) The objective of this thesis is to develop deep learning based 2D and 3D object detection and tracking methods on monocular video and apply them to the context of autonomous vehicles. Actually, when directly using still image detectors to process a video stream, the accuracy suffers from sampled image quality problems. Moreover, generating 3D annotations is time-consuming and expensive due to the data fusion and large numbers of frames. We therefore take advantage of the temporal information in videos such as the object consistency, to improve the performance. The methods should not introduce too much extra computational burden, since the autonomous vehicle demands a real-time performance.Multiple methods can be involved in different steps, for example, data preparation, network architecture and post-processing. First, we propose a post-processing method called heatmap propagation based on a one-stage detector CenterNet for video object detection. Our method propagates the previous reliable long-term detection in the form of heatmap to the upcoming frame. Then, to distinguish different objects of the same class, we propose a frame-to-frame network architecture for video instance segmentation by using the instance sequence queries. The tracking of instances is achieved without extra post-processing for data association. Finally, we propose a semi-supervised learning method to generate 3D annotations for 2D video object tracking dataset. This helps to enrich the training process for 3D object detection. Each of the three methods can be individually applied to leverage image detectors to video applications. We also propose two complete network structures to solve 2D and 3D object detection and tracking on monocular video. Note de contenu : 1- Introduction 2- Video object detection avec la heatmap propagation (propagation de carte de chaleur) 3- Video instance segmentation with instance sequence queries 4- Semi-supervised learning of monocular 3D object detection with 2D video tracking annotations 5- Conclusions and perspectives Numéro de notice : 24072 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Informatique et Télécommunications : Toulouse : 2022 DOI : sans En ligne : https://www.theses.fr/2022ESAE0019 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102136

Pose estimation and 3D reconstruction of vehicles from stereo-images using a subcategory-aware shape prior / Maximilian Alexander Coenen in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 181 (November 2021) . - pp 27 - 47 Titre : Pose estimation and 3D reconstruction of vehicles from stereo-images using a subcategory-aware shape prior Type de document : Article/Communication Auteurs : Maximilian Alexander Coenen, Auteur ; Franz Rottensteiner, Auteur Année de publication : 2021 Article en page(s) : pp 27 - 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] estimation de pose [Termes IGN] modèle stochastique [Termes IGN] problème inverse [Termes IGN] reconstruction 3D [Termes IGN] reconstruction d'objet [Termes IGN] robotique [Termes IGN] véhicule automobile [Termes IGN] vision par ordinateur Résumé : (auteur) The 3D reconstruction of objects is a prerequisite for many highly relevant applications of computer vision such as mobile robotics or autonomous driving. To deal with the inverse problem of reconstructing 3D objects from their 2D projections, a common strategy is to incorporate prior object knowledge into the reconstruction approach by establishing a 3D model and aligning it to the 2D image plane. However, current approaches are limited due to inadequate shape priors and the insufficiency of the derived image observations for a reliable alignment with the 3D model. The goal of this paper is to show how 3D object reconstruction can profit from a more sophisticated shape prior and from a combined incorporation of different observation types inferred from the images. We introduce a subcategory-aware deformable vehicle model that makes use of a prediction of the vehicle type for a more appropriate regularisation of the vehicle shape. A multi-branch CNN is presented to derive predictions of the vehicle type and orientation. This information is also introduced as prior information for model fitting. Furthermore, the CNN extracts vehicle keypoints and wireframes, which are well-suited for model-to-image association and model fitting. The task of pose estimation and reconstruction is addressed by a versatile probabilistic model. Extensive experiments are conducted using two challenging real-world data sets on both of which the benefit of the developed shape prior can be shown. A comparison to state-of-the-art methods for vehicle pose estimation shows that the proposed approach performs on par or better, confirming the suitability of the developed shape prior and probabilistic model for vehicle reconstruction. Numéro de notice : A2021-772 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.07.006 Date de publication en ligne : 14/09/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98829 [article]

The point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1374 - 1391 Titre : The point-descriptor-precedence representation for point configurations and movements Type de document : Article/Communication Auteurs : Amna Qayyum, Auteur ; Bernard De Baets, Auteur ; Muhammad Sulman Baig, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1374 - 1391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] courbe [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] mesurage de distances [Termes IGN] objet mobile [Termes IGN] reconnaissance de formes [Termes IGN] relation topologique [Termes IGN] trafic routier [Termes IGN] véhicule automobile Résumé : (auteur) In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of a system of relational symbols based on two distance descriptors: one representing distance along the curved directed line and the other representing signed orthogonal distance to the curved directed line. The curved directed line represents the direction of the movement of interest. For instance, it could be straight as in the case of driving along a highway or could be curved as in the case of an intersection or a roundabout. Inspired by the Point Calculus, the order between the points on the curved directed line is described by means of a small set of binary relations () acting upon the distance descriptors. We call this representation the Point-Descriptor-Precedence-Static (PDPS) representation at a time point and Point-Descriptor-Precedence-Dynamic (PDPD) representation during a time interval. To illustrate how the proposed approach can be used to represent and analyse curved movements, some basic micro-analysis traffic examples are studied. Finally, we discuss some extensions of our work to highlight the practical benefits of PDP in identifying motion patterns that could be useful in GIS, autonomous vehicles, sports analytics, and gait analysis. Numéro de notice : A2021-453 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1864378 Date de publication en ligne : 11/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1864378 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97882 [article]

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Structure-aware completion of photogrammetric meshes in urban road environment / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)  

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Deep convolutional neural networks for scene understanding and motion planning for self-driving vehicles / Abdelhak Loukkal (2021)  

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A method for urban population density prediction at 30m resolution / Krishnachandran Balakrishnan in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)  

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Probabilistic pose estimation and 3D reconstruction of vehicles from stereo images / Maximilian Alexander Coenen (2020)  

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Scene context-driven vehicle detection in high-resolution aerial images / Chao Tao in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)  

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Development and evaluation of a deep learning model for real-time ground vehicle semantic segmentation from UAV-based thermal infrared imagery / Mehdi Khoshboresh Masouleh in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

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Vehicle detection in aerial images / Michael Ying Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 4 (avril 2019)  

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Rapport d'activité 2018 de l'Institut National de l'Information Géographique et Forestière IGN, 2. Panorama 2018 / Institut national de l'information géographique et forestière (2012 -) (2019)

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De la navigation connectée à la voiture autonome - partie 2 Et mon tout est un véhicule autonome / Hubert d' Erceville in SIGmag, n° 17 (juin 2018)

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