Descripteur
Documents disponibles dans cette catégorie (24)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externesEtendre la recherche sur niveau(x) vers le bas
Evaluating urban intensity through a city information model - intermediate results from an action research project / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VIII-4/W2-2021 ([07/10/2021])
Titre : Evaluating urban intensity through a city information model - intermediate results from an action research project Type de document : Article/Communication Auteurs : Adeline Deprêtre, Auteur ; Florence Jacquinod Année de publication : 2021 Projets : 1-Pas de projet / Conférence : 3D GeoInfo 2021, ISPRS 16th international conference 11/10/2021 14/10/2021 New York City New-York - Etats-Unis OA ISPRS Annals Article en page(s) : pp 153 - 160 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] espace public
[Termes IGN] indicateur
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] planification urbaineRésumé : (auteur) Urban planning is a very complex task, especially considering the many challenges it faces, including an increasing need for housing in response to demographic growth and a need to limit abusive land artificialisation. As part of an interdisciplinary action-research project focused on experimenting with various uses of an existing City Information Model (CIM) for urban design, we are developing a new indicator to characterize urban intensity and a method to quantify it through the City Information Model (CIM) of a French eco-district. Our project is ongoing, and, in this paper, we present intermediate results on the potential of this CIM to support the automated quantification of our urban intensity indicator. We also describe the solutions currently implemented so that our experimental CIM can provide the necessary information for a more complete and automated urban intensity analysis. Finally, we shed light on key issues regarding the use of CIM, specifically CIM made up of various BIM models (of buildings lots and public spaces) for urban analysis at the district scale during the design phase. These issues include the need to generalize BIM entities and to manage property sets and nomenclatures to allow automation of analyses at the district scale, as long as there is no BIM+ data model allowing for urban analysis. Numéro de notice : A2021-739 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-VIII-4-W2-2021-153-2021 En ligne : https://doi.org/10.5194/isprs-annals-VIII-4-W2-2021-153-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98753
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol VIII-4/W2-2021 [07/10/2021] . - pp 153 - 160[article]
Titre : Pedestrian fowl prediction in open public places using graph convolutional network Type de document : Article/Communication Auteurs : Menghang Liu, Auteur ; Luning Li, Auteur ; Qiang Li, Auteur Année de publication : 2021 Article en page(s) : n° 455 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] espace public
[Termes IGN] flux
[Termes IGN] modèle de simulation
[Termes IGN] navigation pédestre
[Termes IGN] planification urbaine
[Termes IGN] réseau neuronal de graphes
[Termes IGN] Shenzhen
[Termes IGN] variation temporelleRésumé : (auteur) Open public places, such as pedestrian streets, parks, and squares, are vulnerable when the pedestrians thronged into the sidewalks. The crowd count changes dynamically over time with various external factors, such as surroundings, weekends, and peak hours, so it is essential to predict the accurate and timely crowd count. To address this issue, this study introduces graph convolutional network (GCN), a network-based model, to predict the crowd flow in a walking street. Compared with other grid-based methods, the model is capable of directly processing road network graphs. Experiments show the GCN model and its extension STGCN consistently and significantly outperform other five baseline models, namely HA, ARIMA, SVM, CNN and LSTM, in terms of RMSE, MAE and R2. Considering the computation efficiency, the standard GCN model was selected to predict the crowd. The results showed that the model obtains superior performances with higher prediction precision on weekends and peak hours, of which R2 are above 0.9, indicating the GCN model can capture the pedestrian features in the road network effectively, especially during the periods with massive crowds. The results will provide practical references for city managers to alleviate road congestion and help pedestrians make smarter planning and save travel time. Numéro de notice : A2021-550 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10070455 Date de publication en ligne : 02/07/2021 En ligne : https://doi.org/10.3390/ijgi10070455 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98073
in ISPRS International journal of geo-information > vol 10 n° 7 (July 2021) . - n° 455[article]
Titre : Dynamic optimization models for displaying outdoor advertisement at the right time and place Type de document : Article/Communication Auteurs : Meng Huang, Auteur ; Zhixiang Fang, Auteur ; Robert Weibel, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1179 - 1204 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Chine
[Termes IGN] espace public
[Termes IGN] modèle dynamique
[Termes IGN] optimisation spatiale
[Termes IGN] point d'intérêt
[Termes IGN] publicité
[Termes IGN] téléphonie mobileRésumé : (auteur) Digital billboards, as a new form of outdoor advertising, has gained popularity in recent years per its revolutionized way to control when and where the specific ads appear. However, this development also demands more complicated optimization for strategic deployments: the advertisers have to not only decide on a set of locations to display their ads, but also when to display them. The existing static optimization approaches become insufficient for this dynamic scenario to match advertisement and intended audience. Therefore, this research proposes three models in a workflow to mine mobile phone data and points of interest (POIs) data and to meet advertising needs in various situations. The three optimization models include a dynamic audience model to maximize the coverage of the target users, a dynamic environment model to maximize the coverage of the target environment, and a dynamic integrated model to maximize the coverage of both target audience and environment. A case study using shopping ads in Wuxue, China tests the three optimalization models. The results show that the proposed models are effective for providing an optimal solution for digital billboard configuration with a greater coverage of the target audience and environment compared to the state-of-the-art static models. Numéro de notice : A2021-386 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1823396 Date de publication en ligne : 24/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1823396 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97643
in International journal of geographical information science IJGIS > vol 35 n° 6 (June 2021) . - pp 1179 - 1204[article]Geometric computer vision: omnidirectional visual and remotely sensed data analysis / Pouria Babahajiani (2021)
Titre : Geometric computer vision: omnidirectional visual and remotely sensed data analysis Type de document : Thèse/HDR Auteurs : Pouria Babahajiani, Auteur ; Moncef Gabbouj, Directeur de thèse Editeur : Tampere [Finlande] : Tampere University Année de publication : 2021 Importance : 147 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-952-03-1979-3 Note générale : bibliographie
Accademic Dissertation, Tampere University, Faculty of Information Technology and Communication Sciences FinlandLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] chaîne de traitement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] effet de profondeur cinétique
[Termes IGN] espace public
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image panoramique
[Termes IGN] image Streetview
[Termes IGN] image terrestre
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] modèle sémantique de données
[Termes IGN] réalité virtuelle
[Termes IGN] scène urbaine
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] vision par ordinateur
[Termes IGN] zone urbaineIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Information about the surrounding environment perceived by the human eye is one of the most important cues enabled by sight. The scientific community has put a great effort throughout time to develop methods for scene acquisition and scene understanding using computer vision techniques. The goal of this thesis is to study geometry in computer vision and its applications. In computer vision, geometry describes the topological structure of the environment. Specifically, it concerns measures such as shape, volume, depth, pose, disparity, motion, and optical flow, all of which are essential cues in scene acquisition and understanding.
This thesis focuses on two primary objectives. The first is to assess the feasibility of creating semantic models of urban areas and public spaces using geometrical features coming from LiDAR sensors. The second objective is to develop a practical Virtual Reality (VR) video representation that supports 6-Degrees-of-Freedom (DoF) head motion parallax using geometric computer vision and machine learning. The thesis’s first contribution is the proposal of semantic segmentation of the 3D LiDAR point cloud and its applications. The ever-growing demand for reliable mapping data, especially in urban environments, has motivated mobile mapping systems’ development. These systems acquire high precision data and, in particular 3D LiDAR point clouds and optical images. A large amount of data and their diversity make data processing a complex task. A complete urban map data processing pipeline has been developed, which annotates 3D LiDAR points with semantic labels. The proposed method is made efficient by combining fast rule-based processing for building and street surface segmentation and super-voxel-based feature extraction and classification for the remaining map elements (cars, pedestrians, trees, and traffic signs). Based on the experiments, the rule-based processing stage provides substantial improvement not only in computational time but also in classification accuracy. Furthermore, two back ends are developed for semantically labeled data that exemplify two important applications: (1) 3D high definition urban map that reconstructs a realistic 3D model using input labeled point cloud, and (2) semantic segmentation of 2D street view images. The second contribution of the thesis is the development of a practical, fast, and robust method to create high-resolution Depth-Augmented Stereo Panoramas (DASP) from a 360-degree VR camera. A novel and complete optical flow-based pipeline is developed, which provides stereo 360-views of a real-world scene with DASP. The system consists of a texture and depth panorama for each eye. A bi-directional flow estimation network is explicitly designed for stitching and stereo depth estimation, which yields state-of-the-art results with a limited run-time budget. The proposed architecture explicitly leverages geometry by getting both optical flow ground-truths. Building architectures that use this knowledge simplifies the learning problem. Moreover, a 6-DoF testbed for immersive content quality assessment is proposed. Modern machine learning techniques have been used to design the proposed architectures addressing many core computer vision problems by exploiting the enriched information coming from 3D scene structures. The architectures proposed in this thesis are practical systems that impact today’s technologies, including autonomous vehicles, virtual reality, augmented reality, robots, and smart-city infrastructures.Note de contenu : 1- Introduction
2- Geometry in Computer Vision
3- Contributions
4- ConclusionNuméro de notice : 28323 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Computing and Electrical Engineering : Tempere, Finland : 2021 DOI : sans En ligne : https://trepo.tuni.fi/handle/10024/131379 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98342
Titre : Lived and perceived space during lock-down in a sensitive map approach Type de document : Article/Communication Auteurs : Laurence Jolivet Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Proceedings of the ICA num. 4 Projets : 1-Pas de projet / Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie OA ISPRS Annals Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartogramme
[Termes IGN] cartographie sensible
[Termes IGN] espace public
[Termes IGN] expérience scientifique
[Termes IGN] sentiment
[Termes IGN] utilisateur civil
[Vedettes matières IGN] CartologieRésumé : (auteur) The first lock-down in France due to the Covid-19 pandemic happened during spring 2020. It meant restrictions for everyone regarding reachable space and possible time length outside home. The seminar of sensitive mapping taking place in École des hautes études en sciences sociales (EHESS) went online and proposed an exercise to investigate the consequences of these statutory restrictions on individual lived and perceived space. The defined protocol of the exercise was based on the framework of the sensitive map approach. This approach adapts the principles of conventional cartography so that to favour personal information selection and design. Each participant of the seminar had the task to map their space. Displayed information should concern meaningful elements from their spatial environment. Other targeted information was sensitive information including emotions, feelings, and opinions as well as perceived elements from the five senses. The resulted map corpus offers diverse mapping creations. Each map contains several graphic items. Items are mainly cartographical displays enriched with non-cartographical drawings, pictures, photos, records, charts. Techniques were mixed: pen, fabrics, computer-based. The themes of displayed elements are about spatially-stable features like the dwelling, buildings remained open, green spaces, and about ephemeral and sensitive information like social interactions, people, perceived sounds, smells and feelings about the lock-down situation and the pandemic. Some maps have used or were inspired by topographic maps. Though in most maps, distances and topology are subjective. Sensitive mapping appeared as an interesting approach to collect individual testimonies and might be complementary to statistical studies. Numéro de notice : C2021-056 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-4-50-2021 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.5194/ica-proc-4-50-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99435 Qualification des données Stéréopolis et étude d'un algorithme de détection d'objets / Guillaume Curtet (2016)
PermalinkPermalinkPermalinkUrban Net Project, Chronotope « Aménagement spatio-temporel pour des villes résilientes » / Jean Soumagne (2013)
Permalink
