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Trajectory drift–compensated solution of a stereo RGB-D mapping system / Shengjun Tang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 6 (June 2020) . - pp 359 - 372 Titre : Trajectory drift–compensated solution of a stereo RGB-D mapping system Type de document : Article/Communication Auteurs : Shengjun Tang, Auteur ; Qing Zhu, Auteur ; You Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 359 - 372 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] compensation [Termes IGN] image RVB [Termes IGN] itération [Termes IGN] optimisation (mathématiques) [Termes IGN] reconstruction 3D Résumé : (Auteur) Multiple sensors are commonly used for three-dimensional (3D)-mapping or robotic-vision applications, as they provide a larger field of view and sufficient observations to fulfill frame-registration and map-updating tasks. However, the data sequences generated by multiple sensors can be inconsistent and contain significant time drift. In this paper, we describe the trajectory drift–compensated strategy that we designed to eliminate the influence of time drift between sensors, remove the inconsistency between the sequences from various sensors, and thereby generate a coarse-to-fine procedure for robust camera-tracking based on two-dimensional–3D observations from stereo sensors. We present the mathematical analysis of the iterative optimizations for pose tracking in a stereo red, green, blue plus depth (RGB-D) camera. Finally, complex indoor scenario experiments demonstrate the efficiency of the proposed stereo RGB-D simultaneous localization and mapping solution. The results verify that the proposed stereo RGB-D mapping solution effectively improves the accuracies of both camera-tracking and 3D reconstruction. Numéro de notice : A2020-241 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.6.359 Date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.14358/PERS.86.6.359 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95199 [article]

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Geometric integration of high-resolution satellite imagery and airborne LiDAR data for improved geopositioning accuracy in metropolitan areas / Bo Wu in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 139 - 151 Titre : Geometric integration of high-resolution satellite imagery and airborne LiDAR data for improved geopositioning accuracy in metropolitan areas Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Shengjun Tang, Auteur ; Qing Zhu, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 139 - 151 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] géométrie de l'image [Termes IGN] Hong-Kong [Termes IGN] image à très haute résolution [Termes IGN] image Pléiades [Termes IGN] image ZiYuan-3 [Termes IGN] intégration de données [Termes IGN] milieu urbain [Termes IGN] précision du positionnement Résumé : (auteur) High-resolution satellite imagery (HRSI) and airborne light detection and ranging (LiDAR) data are widely used for deriving 3D spatial information. However, the 3D spatial information derived from them in the same area can be inconsistent. Considering HRSI and LiDAR datasets taken from metropolitan areas as a case study, this paper presents a novel approach to the geometric integration of HRSI and LiDAR data to reduce their inconsistencies and improve their geopositioning accuracy. First, the influences of HRSI’s individual rational polynomial coefficients (RPCs) on geopositioning accuracies are analyzed and the RPCs that dominate those accuracies are identified. The RPCs are then used as inputs in the geometric integration model together with the tie points identified in stereo images and LiDAR ground points. A local vertical constraint and a local horizontal constraint are also incorporated in the model to ensure vertical and horizontal consistency between the two datasets. The model improves the dominating RPCs and the ground coordinates of the LiDAR points, decreasing the inconsistencies between the two datasets and improving their geopositioning accuracy. Experiments were conducted using ZY-3 and Pleiades-1 imagery and the corresponding airborne LiDAR data in Hong Kong. The results verify that the geometric integration model effectively improves the geopositioning accuracies of both types of imagery and the LiDAR points. Furthermore, the model enables the full comparative and synergistic use of remote sensing imagery and laser scanning data collected from different platforms and sensors. Numéro de notice : A2015-861 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.09.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.09.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79242 [article]