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Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring / Mohammad Omidalizarandi in Journal of applied geodesy, vol 13 n° 2 (April 2019)  

Public [article]  inJournal of applied geodesy > vol 13 n° 2 (April 2019) . - pp 105 - 130 Titre : Robust external calibration of terrestrial laser scanner and digital camera for structural monitoring Type de document : Article/Communication Auteurs : Mohammad Omidalizarandi, Auteur ; Boris Kargoll, Auteur ; Jens-André Paffenholz, Auteur ; Ingo Neumann, Auteur Année de publication : 2019 Article en page(s) : pp 105 - 130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme espérance-maximisation [Termes IGN] déformation de la croute terrestre [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] élément d'orientation externe [Termes IGN] méthode des moindres carrés [Termes IGN] modèle de Gauss-Helmert [Termes IGN] modèle de Gauss-Markov [Termes IGN] orthoimage [Termes IGN] semis de points Résumé : (Auteur) In the last two decades, the integration of a terrestrial laser scanner (TLS) and digital photogrammetry, besides other sensors integration, has received considerable attention for deformation monitoring of natural or man-made structures. Typically, a TLS is used for an area-based deformation analysis. A high-resolution digital camera may be attached on top of the TLS to increase the accuracy and completeness of deformation analysis by optimally combining points or line features extracted both from three-dimensional (3D) point clouds and captured images at different epochs of time. For this purpose, the external calibration parameters between the TLS and digital camera needs to be determined precisely. The camera calibration and internal TLS calibration are commonly carried out in advance in the laboratory environments. The focus of this research is to highly accurately and robustly estimate the external calibration parameters between the fused sensors using signalised target points. The observables are the image measurements, the 3D point clouds, and the horizontal angle reading of a TLS. In addition, laser tracker observations are used for the purpose of validation. The functional models are determined based on the space resection in photogrammetry using the collinearity condition equations, the 3D Helmert transformation and the constraint equation, which are solved in a rigorous bundle adjustment procedure. Three different adjustment procedures are developed and implemented: (1) an expectation maximization (EM) algorithm to solve a Gauss-Helmert model (GHM) with grouped t-distributed random deviations, (2) a novel EM algorithm to solve a corresponding quasi-Gauss-Markov model (qGMM) with t-distributed pseudo-misclosures, and (3) a classical least-squares procedure to solve the GHM with variance components and outlier removal. The comparison of the results demonstrates the precise, reliable, accurate and robust estimation of the parameters in particular by the second and third procedures in comparison to the first one. In addition, the results show that the second procedure is computationally more efficient than the other two. Numéro de notice : A2019-145 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2018-0038 Date de publication en ligne : 02/02/2019 En ligne : https://doi.org/10.1515/jag-2018-0038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92472 [article]

Geo-referencing point clouds with transformational and positional uncertainties / Jens-André Paffenholz in Journal of applied geodesy, vol 6 n° 1 (January 2012)  

Public [article]  inJournal of applied geodesy > vol 6 n° 1 (January 2012) . - pp 33 - 46 Titre : Geo-referencing point clouds with transformational and positional uncertainties Type de document : Article/Communication Auteurs : Jens-André Paffenholz, Auteur ; Kwang-Ho Bae, Auteur Année de publication : 2012 Article en page(s) : pp 33 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] géoréférencement [Termes IGN] incertitude géométrique [Termes IGN] propagation d'erreur [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre Résumé : (auteur) The paper presents an iterative matching method to improve a direct geo-referencing approach for stationary terrestrial 3D laser scans by means of the positional and transformational uncertainties of two 3D point clouds. In this approach, a geo-referenced point cloud from a station inherits the following stochastic information: (1) transformational uncertainties from processed GNSS data through the Kalman filter and (2) positional uncertainties through the range and angular uncertainties from the terrestrial laser scanner as well as the incident angle of the laser beam to a surface. This stochastic information from two (pre-) geo-referenced 3D point clouds is implemented within a novel iterative matching algorithm, named Geo-referencing ICP with Helmert 3D transformation, for subsequent post-processing procedures such as segmentation and further calibration. Numéro de notice : A2012-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2011-0010 En ligne : https://doi.org/10.1515/jag-2011-0010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84545 [article]