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Exploiting light directionality for image-based 3D reconstruction of non-collaborative surfaces / Ali Karami in Photogrammetric record, vol 37 n° 177 (March 2022)
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Titre : Exploiting light directionality for image-based 3D reconstruction of non-collaborative surfaces Type de document : Article/Communication Auteurs : Ali Karami, Auteur ; Fabio Menna, Auteur ; Fabio Remondino, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 111 - 138 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] axe de prise de vue
[Termes IGN] étalonnage
[Termes IGN] figure géométrique
[Termes IGN] point d'appui
[Termes IGN] points homologues
[Termes IGN] rayonnement lumineux
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'objet
[Termes IGN] semis de points
[Termes IGN] textureRésumé : (auteur) Three-dimensional (3D) measurement of non-collaborative surfaces is still an open research topic. This paper investigates and quantifies for the first time the effect of light directionality and fusion of multiple images as a method to improve the quality of photogrammetric 3D reconstruction. For this aim, an image acquisition system that employs multiple light sources was developed to highlight the roughness and microstructures of the object under investigation. Images were captured at various grazing angles to highlight the local surface roughness and microstructures. Individual point clouds, created using images taken at different grazing angles, were produced using dense image-matching techniques. These point clouds were then compared against different 3D photogrammetric reconstructions obtained from a pre-processing of the acquired images based on diffuse lighting, median and average images. Experiments showed that exploiting light directionality significantly improves image-matching quality. Furthermore, depending on the light direction, the root mean square (RMS) error of the 3D surfaces obtained using the proposed system were up to 50% less than those created by traditional diffuse lighting. Numéro de notice : A2022-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12400 Date de publication en ligne : 07/03/2022 En ligne : https://doi.org/10.1111/phor.12400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100218
in Photogrammetric record > vol 37 n° 177 (March 2022) . - pp 111 - 138[article]Urban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration / Ming Guo in Geo-spatial Information Science, vol 24 n° 4 (October 2021)
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Titre : Urban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration Type de document : Article/Communication Auteurs : Ming Guo, Auteur ; Yuquan Zhou, Auteur ; Jianghong Zhao, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 558 - 579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] coordonnées GNSS
[Termes IGN] couplage GNSS-INS
[Termes IGN] données lidar
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] orientation du capteur
[Termes IGN] précision des mesures
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] station GNSS
[Termes IGN] système de numérisation mobile
[Termes IGN] zone urbaineRésumé : (auteur) The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measurement accuracy has always been a research hotspot in the industry. This paper proposes a position and attitude calibration method with error correction based on the combination of the feature point and feature surface. First, the initial value of the spatial position relationship between each sensor of MMS is obtained by close-range photogrammetry. Second, the optimal solution for error correction is calculated by feature points in global coordinates jointly measured with International GNSS Service (IGS) stations. Then, the final transformation parameters are solved by combining the initial values obtained originally, thereby realizing the rapid calibration of the MMS. Finally, it analyzed the RMSE of MMS point cloud after calibration, and the results demonstrate the feasibility of the calibration approach proposed by this method. Under the condition of a single measurement sensor accuracy is low, the plane and elevation absolute accuracy of the point cloud after calibration can reach 0.043 m and 0.072 m, respectively, and the relative accuracy is smaller than 0.02 m. It meets the precision requirements of data acquisition for MMS. It is of great significance for promoting the development of MMS technology and the application of some novel techniques in the future, such as autonomous driving, digital twin city, urban brain et al. Numéro de notice : A2021-128 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10095020.2021.1924084 Date de publication en ligne : 20/08/2021 En ligne : https://doi.org/10.1080/10095020.2021.1924084 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99354
in Geo-spatial Information Science > vol 24 n° 4 (October 2021) . - pp 558 - 579[article]A unified framework of bundle adjustment and feature matching for high-resolution satellite images / Xiao Ling in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)
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Titre : A unified framework of bundle adjustment and feature matching for high-resolution satellite images Type de document : Article/Communication Auteurs : Xiao Ling, Auteur ; Xu Huang, Auteur ; Rongjun Qin, Auteur Année de publication : 2021 Article en page(s) : pp 485 - 490 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] appariement d'images
[Termes IGN] compensation par faisceaux
[Termes IGN] corrélation à l'aide de traits caractéristiques
[Termes IGN] image à haute résolution
[Termes IGN] orientation du capteur
[Termes IGN] précision radiométriqueRésumé : (Auteur) Bundle adjustment (BA) is a technique for refining sensor orientations of satellite images, while adjustment accuracy is correlated with feature matching results. Feature matching often contains high uncertainties in weak/repeat textures, while BA results are helpful in reducing these uncertainties. To compute more accurate orientations, this article incorporates BA and feature matching in a unified framework and formulates the union as the optimization of a global energy function so that the solutions of the BA and feature matching are constrained with each other. To avoid a degeneracy in the optimization, we propose a comprised solution by breaking the optimization of the global energy function into two-step suboptimizations and compute the local minimums of each suboptimization in an incremental manner. Experiments on multi-view high-resolution satellite images show that our proposed method outperforms state-of-the-art orientation techniques with or without accurate least-squares matching. Numéro de notice : A2021-571 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.7.485 Date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.14358/PERS.87.7.485 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98163
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 7 (July 2021) . - pp 485 - 490[article]Réservation
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Titre : Benefiting from local rigidity in 3D point cloud processing Type de document : Thèse/HDR Auteurs : Zan Gojcic, Auteur Editeur : Zurich : Eidgenossische Technische Hochschule ETH - Ecole Polytechnique Fédérale de Zurich EPFZ Année de publication : 2021 Importance : 141 p. Format : 21 x 30 cm Note générale : bibliographie
A thesis submitted to attain the degree of Doctor of Sciences of ETH ZurichLangues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] capteur actif
[Termes IGN] champ vectoriel
[Termes IGN] déformation d'image
[Termes IGN] données lidar
[Termes IGN] effondrement de terrain
[Termes IGN] enregistrement de données
[Termes IGN] filtrage du bruit
[Termes IGN] flux
[Termes IGN] image 3D
[Termes IGN] navigation autonome
[Termes IGN] orientation du capteur
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] téléphone intelligent
[Termes IGN] traitement de nuage de points
[Termes IGN] voxelIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Incorporating 3D understanding and spatial reasoning into (intelligent) algorithms is crucial for solving several tasks in fields such as engineering geodesy, risk assessment, and autonomous driving. Humans are capable of reasoning about 3D spatial relations even from a single 2D image. However, making the priors that we rely on explicit and integrating them into computer programs is very challenging. Operating directly on 3D input data, such as 3D point clouds, alleviates the need to lift 2D data into a 3D representation within the task-specific algorithm and hence reduces the complexity of the problem. The 3D point clouds are not only a better-suited input data representation, but they are also becoming increasingly easier to acquire. Indeed, nowadays, LiDAR sensors are even integrated into consumer devices such as mobile phones. However, these sensors often have a limited field of view, and hence multiple acquisitions are required to cover the whole area of interest. Between these acquisitions, the sensor has to be moved and pointed in a different direction. Moreover, the world that surrounds us is also dynamic and might change as well. Reasoning about the motion of both the sensor and the environment, based on point clouds acquired in two-time steps, is therfore an integral part of point cloud processing. This thesis focuses on incorporating rigidity priors into novel deep learning based approaches for dynamic 3D perception from point cloud data. Specifically, the tasks of point cloud registration, deformation analysis, and scene flow estimation are studied. At first, these tasks are incorporated into a common framework where the main difference is in the level of rigidity assumptions that are imposed on the motion of the scene or
the acquisition sensor. Then, the tasks specific priors are proposed and incorporated into novel deep learning architectures. While the global rigidity can be assumed in point cloud registration, the motion patterns in deformation analysis and scene flow estimation are more complex. Therefore, the global rigidity prior has to be relaxed to local or instancelevel rigidity, respectively. Rigidity priors not only add structure to the aforementioned tasks, which prevents physically implausible estimates and improves the generalization of the algorithms, but in some cases also reduce the supervision requirements. The proposed approaches were quantitatively and qualitatively evaluated on several datasets, and they yield favorable performance compared to the state-of-the-art.Numéro de notice : 28660 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD : Sciences : ETH Zurich : 2021 DOI : sans En ligne : https://www.research-collection.ethz.ch/handle/20.500.11850/523368 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99817 Improving GEDI footprint geolocation using a high resolution digital terrain model / Anouk Schleich (2021)
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Titre : Improving GEDI footprint geolocation using a high resolution digital terrain model Type de document : Article/Communication Auteurs : Anouk Schleich, Auteur ; Maxime Soma, Auteur ; Sylvie Durrieu, Auteur ; Cédric Vega , Auteur ; Jean-Pierre Renaud, Auteur ; Olivier Bouriaud
, Auteur
Editeur : Vienne [Autriche] : Technische Universität Wien Année de publication : 2021 Collection : Geowissenschaftliche Mitteilungen, ISSN 1811-8380 num. 104 Projets : TOSCA SLIM / Conférence : SilviLaser 2021, 17th conference on Lidar Applications for Assessing and Managing Forest Ecosystems 28/09/2021 30/09/2021 Vienne + online Autriche open access proceedings Importance : pp 179 - 181 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] fauchée
[Termes IGN] géoréférencement
[Termes IGN] Global Ecosystem Dynamics Investigation lidar
[Termes IGN] modèle numérique de terrainRésumé : (auteur) [introduction] In 2018, NASA launched the Global Ecosystem Dynamics Investigation (GEDI) mission, a high resolution lidar system installed onboard the International Space Station (ISS). It is producing high quality 3D observations of the Earth surface structure, which are highly relevant to study forest ecosystems at a global scale (Qi et al. 2019). GEDI data is composed of 25 m diameter circular footprints for which the waveform of the received energy intensity returned by the ground is recorded. Each GEDI footprint is georeferenced and its positioning accuracy (for version 1 releases) is estimated at 15-20 m in planimetry with a systematic component of 8-10 m and a noise of the order of 8 m (1). A final horizontal geolocation accuracy of 8 m is expected after further processing in the final version (Dubayah et al. 2020). Compared to most other spatial satellites the ISS is much closer to earth, causing more variations in its orientation and altitude. Therefore, geolocating data acquired by ISS sensors is more diffucult than geolocating data aquired by satellites (Dou et al. 2014). An improved geolocation of GEDI data is mandatory to evaluate their quality, by comparison with other earth observation data or field measurements, and to further facilitate their integration in ecosystem monitoring approaches. We propose a method to improve the georeferencing of GEDI footprints using a precise Digital Terrain Model (DTM). Numéro de notice : C2021-053 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.34726/wim.1973 Date de publication en ligne : 01/12/2021 En ligne : https://doi.org/10.34726/wim.1973 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99223 On-Orbit Calibration of Terra MODIS VIS Bands Using Polarization-Corrected Desert Observations / Amit Angal in IEEE Transactions on geoscience and remote sensing, vol 58 n° 8 (August 2020)
PermalinkPermalinkGeometric accuracy improvement of WorldView‐2 imagery using freely available DEM data / Mateo Gašparović in Photogrammetric record, vol 34 n° 167 (September 2019)
PermalinkExplanation for the seam line discontinuity in terrestrial laser scanner point clouds / Derek D. Lichti in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkDigital surface model generation from high resolution multi-view stereo satellite imagery / Ke Gong in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 5 (May 2019)
PermalinkAutomatic sensor orientation using horizontal and vertical line feature constraints / Yanbiao Sun in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)
PermalinkPermalinkA spatiotemporal calculus for reasoning about land-use trajectories / Adeline Marinho Maciel in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)
PermalinkPolarization orientation angle and polarimetric SAR scattering characteristics of steep terrain / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
PermalinkOdometer, low-cost inertial sensors, and four-GNSS data to enhance PPP and attitude determination / Zhouzheng Gao in GPS solutions, vol 22 n° 3 (July 2018)
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