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Comparative usability of an augmented reality sandtable and 3D GIS for education / Antoni B. Moore in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
[article]
Titre : Comparative usability of an augmented reality sandtable and 3D GIS for education Type de document : Article/Communication Auteurs : Antoni B. Moore, Auteur ; Benjamin Daniel, Auteur ; greg Leonard, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 229 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] enseignement supérieur
[Termes IGN] hydrologie
[Termes IGN] modèle numérique de terrain
[Termes IGN] modélisation 3D
[Termes IGN] Nouvelle-Zélande
[Termes IGN] réalité augmentée
[Termes IGN] réalité de terrain
[Termes IGN] réalité virtuelle
[Termes IGN] sable
[Termes IGN] test de performanceRésumé : (auteur) Augmented Reality (AR) sandtables facilitate the shaping of sand to form a surface that is transformed into a digital terrain map which is projected back onto the sand. Although a mature technology, there are still few instances of sandtables being used in surface analysis. Fundamentally there has not been any reported formal assessment of how well sandtables perform in an educational context compared to other conventional learning environments. We compared learning outcomes from using an AR sandtable versus a conventional 3D GIS to convey key concepts in terrain and hydrological analyses via usability and knowledge testing. Overall results from students at a research-intensive New Zealand university reveal a faster task performance and more learning satisfaction when using the sandtable to undertake experimental tasks. Effectiveness and knowledge quiz results revealed no significant difference between the technologies though there was a trend for more accurate answers with 3D GIS tasks. Student learning wise, the sandtable integrated core concepts (especially morphometry) more effectively though both technologies were otherwise similar. We conclude that sandtables have high potential in geospatial teaching, fostering accessible and engaging means of introducing terrain and hydrological concepts, prior to undertaking a more accurate and precise surface analysis with 3D GIS. Numéro de notice : A2020-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1656810 Date de publication en ligne : 27/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1656810 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94481
in International journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 229 - 250[article]Tree annotations in LiDAR data using point densities and convolutional neural networks / Ananya Gupta in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
[article]
Titre : Tree annotations in LiDAR data using point densities and convolutional neural networks Type de document : Article/Communication Auteurs : Ananya Gupta, Auteur ; Jonathan Byrne, Auteur ; David Moloney, Auteur Année de publication : 2020 Article en page(s) : pp 971 - 981 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données lidar
[Termes IGN] Dublin (Irlande ; ville)
[Termes IGN] extraction d'arbres
[Termes IGN] image spectrale
[Termes IGN] Montréal (Québec)
[Termes IGN] segmentation
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] voxel
[Termes IGN] zone urbaineRésumé : (auteur) LiDAR provides highly accurate 3-D point clouds. However, data need to be manually labeled in order to provide subsequent useful information. Manual annotation of such data is time-consuming, tedious, and error prone, and hence, in this article, we present three automatic methods for annotating trees in LiDAR data. The first method requires high-density point clouds and uses certain LiDAR data attributes for the purpose of tree identification, achieving almost 90% accuracy. The second method uses a voxel-based 3-D convolutional neural network on low-density LiDAR data sets and is able to identify most large trees accurately but struggles with smaller ones due to the voxelization process. The third method is a scaled version of the PointNet++ method and works directly on outdoor point clouds and achieves an F score of 82.1% on the ISPRS benchmark data set, comparable to the state-of-the-art methods but with increased efficiency. Numéro de notice : A2020-095 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2942201 Date de publication en ligne : 11/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2942201 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94658
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 2 (February 2020) . - pp 971 - 981[article]
Titre : Advances in digital image correlation (DIC) Type de document : Monographie Auteurs : Jean-Noël Perie, Éditeur scientifique ; Jean-Charles Passieux, Éditeur scientifique Editeur : Londres : Applied Science Publishers Année de publication : 2020 Importance : 252 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03928-514-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] corrélation croisée normalisée
[Termes IGN] Déformation
[Termes IGN] données de terrain
[Termes IGN] étalonnage
[Termes IGN] modélisation 3D
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] prise de vues en accéléré
[Termes IGN] tomographieRésumé : (auteur) Digital image correlation (DIC) has become the most popular full field measurement technique in experimental mechanics. It is a versatile and inexpensive measurement method that provides a large amount of experimental data. Because DIC takes advantage of a huge variety of image modalities, the technique allows covering a wide range of space and time scales. Stereo extends the scope of DIC to non-planar cases, which are more representative of industrial use cases. With the development of tomography, digital volume correlation now provides access to volumetric data, enabling the study of the inner behavior of materials and structures.However, the use of DIC data to quantitatively validate models or accurately identify a set of constitutive parameters remains challenging. One of the reasons lies in the compromises between measurement resolution and spatial resolution. Second, the question of the boundary conditions is still open. Another reason is that the measured displacements are not directly comparable with usual simulations. Finally, the use of full field data leads to new computational challenges. Note de contenu : 1- Special issue on advances in digital image correlation (DIC)
2- Measurement of super-pressure balloon deformation with simplified digital image correlation
3- A cross-dichroic-prism-based multi-perspective digital image correlation system
4- Laboratory observations of repeated interactions between ruptures and the fault bend prior to the overall stick-slip instability based on a digital image correlation method
5- Application of 3D digital image correlation for development and validation of FEM model of self-supporting arch structures
6- Experimental study on the fracture process zone characteristics in concrete utilizing DIC and AE methods
7- 3D strain and elasticity measurement of layered biomaterials by optical coherence
elastography based on digital volume correlation and virtual fields method
8- 3D strain mapping of opaque materials using an improved digital volumetric speckle
photography technique with X-Ray microtomography
9- Enhanced digital image correlation analysis of ruptures with enforced traction continuity conditions across interfaces
10- Application of the non-contact video gauge on the mechanical properties test for steel cable at elevated temperature
11- New four points initialization for digital image correlation in metal-sheet
strain measurements
12- Dynamic response of copper plates subjected to underwater impulsive loading
13- Gradient correlation functions in digital image correlation
14- Image classification for automated image cross-correlation applications in the geosciences
15- Measurement of interlaminar tensile strength and elastic properties of composites using open-hole compression testing and digital image correlation
16- Digital image correlation applications in composite automated manufacturing, inspection, and testing
17- A method for calibrating a digital image correlation system for full-field strain
measurements during large deformationsNuméro de notice : 25933 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie En ligne : https://doi.org/10.3390/books978-3-03928-515-0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96241 Cattle detection and counting in UAV images based on convolutional neural networks / Wen Shao in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)
[article]
Titre : Cattle detection and counting in UAV images based on convolutional neural networks Type de document : Article/Communication Auteurs : Wen Shao, Auteur ; Rei Kawakami, Auteur ; Ryota Yoshihashi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 31 - 52 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bovin
[Termes IGN] chevauchement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] comptage
[Termes IGN] détection d'objet
[Termes IGN] image captée par drone
[Termes IGN] modélisation 3DRésumé : (auteur) For assistance with grazing cattle management, we propose a cattle detection and counting system based on Convolutional Neural Networks (CNNs) using aerial images taken by an Unmanned Aerial Vehicle (UAV). To improve detection performance, we take advantage of the fact that, with UAV images, the approximate size of the objects can be predicted when the UAV’s height from the ground can be assumed to be roughly constant. We resize an image to be fed into the CNN to an optimum resolution determined by the object size and the down-sampling rate of the network, both in training and testing. To avoid repetition of counting in images that have large overlaps to adjacent ones and to obtain the accurate number of cattle in an entire area, we utilize a three-dimensional model reconstructed by the UAV images for merging the detection results of the same target. Experiments show that detection performance is greatly improved when using the optimum input resolution with an F-measure of 0.952, and counting results are close to the ground truths when the movement of cattle is approximately stationary compared to that of the UAV’s. Numéro de notice : A2020-209 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2019.1624858 Date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1080/01431161.2019.1624858 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94891
in International Journal of Remote Sensing IJRS > vol 41 n° 1 (01 - 08 janvier 2020) . - pp 31 - 52[article]
Titre : Co-visualization of air temperature and urban data for visual exploration Type de document : Article/Communication Auteurs : Jacques Gautier , Auteur ; Mathieu Brédif , Auteur ; Sidonie Christophe , Auteur Editeur : New-York : IEEE Computer society Année de publication : 2020 Projets : URCLIM / Masson, Valéry Conférence : IEEE VIS 2020, (VAST, INFOVIS, SCIVIS), premier forum for advances in visualization and visual analytics 25/10/2020 30/10/2020 en ligne vers VIS.org Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] distribution spatiale
[Termes IGN] exploration de données géographiques
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] morphologie urbaine
[Termes IGN] rendu (géovisualisation)
[Termes IGN] représentation graphique
[Termes IGN] température de l'air
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Urban climate data remain complex to analyze regarding their spatial distribution. The co-visualization of simulated air temperature into urban models could help experts to analyze horizontal and vertical spatial distributions. We design a co-visualization framework enabling simulated air temperature data exploration, based on the graphic representation of three types of geometric proxies, and their co-visualization with a 3D urban model with various possible rendering styles. Through this framework, we aim at allowing meteorological researchers to visually analyze and interpret the relationships between simulated air temperature data and urban morphology. Numéro de notice : C2020-005 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : VIS 2020 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/VIS47514.2020.00021 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.1109/VIS47514.2020.00021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96161 Documents numériques
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