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Research on 3D model reconstruction based on a sequence of cross-sectional images / Zhiguo Dong in Machine Vision and Applications, vol 32 n°4 (July 2021)  

Public [article]  inMachine Vision and Applications > vol 32 n°4 (July 2021) . - n° 92 Titre : Research on 3D model reconstruction based on a sequence of cross-sectional images Type de document : Article/Communication Auteurs : Zhiguo Dong, Auteur ; Xiaobo Wu, Auteur ; Zhipeng Ma, Auteur Année de publication : 2021 Article en page(s) : n° 92 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse infrapixellaire [Termes IGN] B-Spline [Termes IGN] détection de contours [Termes IGN] modélisation 3D [Termes IGN] reconstruction 3D [Termes IGN] reconstruction d'objet [Termes IGN] semis de points Résumé : (auteur) It is often difficult to obtain the high-precision inner cavity contour size and 3D model of parts and components in reverse engineering. This paper proposes a method that uses a sequence of section images of a part to reconstruct their 3D models. This method cuts the part layer by layer to obtain the sectional images and extracts the 3D information of the sectional image contours to generate point clouds. These point clouds are then used to reconstruct a 3D model of the part. High contrast material is used to embed the target part for pre-processing. A machining centre was used to mill the part layer by layer vertically to acquire high precision section profile images. The improved Canny edge detection operator was combined with the spatial moment sub-pixel subdivision algorithm to improve the edge detection accuracy. The camera imaging model algorithm transforms the coordinates of the image edge position to obtain a high-precision 3D point cloud of the part. The 3D solid model of the target part was obtained using NURBS surface reconstruction. The results show that the 3D model reconstruction method using the profile sequence of the cross-sectional images is independent of the complexity of the part’s structure and the complete internal structure of the part can be obtained. The proposed edge detection algorithm significantly refines the edge position of the contours in the cross-sectional image and the measurement accuracy was improved. This method improves the minimum deviation to 50 μm. The shape accuracy of roundness, cylindricity and perpendicularity of the structure is high. The proposed method can meet the reverse precision requirements in general precision machining. Numéro de notice : A2021-635 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00138-021-01220-7 Date de publication en ligne : 11/06/2021 En ligne : https://doi.org/10.1007/s00138-021-01220-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98299 [article]

Stochastic models for geodesy and geoinformation science / Frank Neitzel (2021)    

Public Titre : Stochastic models for geodesy and geoinformation science Type de document : Monographie Auteurs : Frank Neitzel, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 200 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03943-982-9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] B-Spline [Termes IGN] covariance [Termes IGN] erreur de phase [Termes IGN] incertitude de mesurage [Termes IGN] interférométrie à très grande base [Termes IGN] méthode de Monte-Carlo [Termes IGN] méthode des moindres carrés [Termes IGN] modèle stochastique [Termes IGN] phase GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] réseau géodésique [Termes IGN] télémétrie laser aéroporté Résumé : (éditeur) In geodesy and geoinformation science, as well as in many other technical disciplines, it is often not possible to directly determine the desired target quantities. Therefore, the unknown parameters must be linked with the measured values by a mathematical model which consists of the functional and the stochastic models. The functional model describes the geometrical–physical relationship between the measurements and the unknown parameters. This relationship is sufficiently well known for most applications. With regard to the stochastic model, two problem domains of fundamental importance arise: 1. How can stochastic models be set up as realistically as possible for the various geodetic observation methods and sensor systems? 2. How can the stochastic information be adequately considered in appropriate least squares adjustment models? Further questions include the interpretation of the stochastic properties of the computed target values with regard to precision and reliability and the use of the results for the detection of outliers in the input data (measurements). In this Special Issue, current research results on these general questions are presented in ten peer-reviewed articles. The basic findings can be applied to all technical scientific fields where measurements are used for the determination of parameters to describe geometric or physical phenomena. Note de contenu : 1- Total least-squares collocation: An optimal estimation technique for the EIV-model with prior information 2- Weighted Total Least Squares (WTLS) Solutions for straight line fitting to 3D point data 3- Stochastic properties of confidence ellipsoids after least squares adjustment, derived from GUM analysis and Monte Carlo simulations 4- Mean shift versus variance inflation approach for outlier detection—A comparative study 5- A generic approach to covariance function estimation using ARMA-models 6- Evaluation of VLBI observations with sensitivity and robustness analyses 7- Variance reduction of sequential Monte Carlo approach for GNSS phase bias estimation 8- Automatic calibration of process noise matrix and measurement noise covariance for multi-GNSS precise point positioning 9- Elementary error model applied to terrestrial laser scanning measurements: Study case arch Dam Kops 10- On estimating the hurst parameter from least-squares residuals. Case study: Correlated terrestrial laser scanner range noise Numéro de notice : 28459 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE/POSITIONNEMENT Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03943-982-9 En ligne : http://dx.doi.org/10.3390/books978-3-03943-982-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99044

A spatio-temporal deformation model for laser scanning point clouds / Corinna Harmening in Journal of geodesy, vol 94 n°2 (February 2020)  

Public [article]  inJournal of geodesy > vol 94 n°2 (February 2020) Titre : A spatio-temporal deformation model for laser scanning point clouds Type de document : Article/Communication Auteurs : Corinna Harmening, Auteur ; Hans Neuner, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] B-Spline [Termes IGN] collocation par moindres carrés [Termes IGN] déformation de surface [Termes IGN] incertitude de mesurage [Termes IGN] modèle de déformation tectonique [Termes IGN] modèle stochastique [Termes IGN] modélisation spatio-temporelle [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre [Termes IGN] variogramme Résumé : (auteur) The establishment of the terrestrial laser scanner changed the analysis strategies in engineering geodesy from point-wise approaches to areal ones. During recent years, a multitude of developments regarding a laser scanner-based geometric state description were made. However, the areal deformation analysis still represents a challenge. In this paper, a spatio-temporal deformation model is developed, combining the estimation of B-spline surfaces with the stochastic modelling of deformations. The approach’s main idea is to model the acquired measuring object by means of three parts, similar to a least squares collocation: a deterministic trend, representing the undistorted object, a stochastic signal, describing a locally homogeneous deformation process, and the measuring noise, accounting for uncertainties caused by the measuring process. Due to the stochastic modelling of the deformations in the form of distance-depending variograms, the challenge of defining identical points within two measuring epochs is overcome. Based on the geodetic datum defined by the initial trend surface, a point-to-surface- and a point-to-point-comparison of the acquired data sets is possible, resulting in interpretable and meaningful deformation metrics. Furthermore, following the basic ideas of a least squares collocation, the deformation model allows a time-related space-continuous description as well as a space- and time-continuous prediction of the deformation. The developed approach is validated using simulated data sets, and the respective results are analysed and compared with respect to nominal surfaces. Numéro de notice : A2020-151 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01352-0 Date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1007/s00190-020-01352-0 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94784 [article]

Real-time sea-level monitoring using Kalman filtering of GNSS-R data / Joakim Strandberg in GPS solutions, vol 23 n° 3 (July 2019)  

Public [article]  inGPS solutions > vol 23 n° 3 (July 2019) Titre : Real-time sea-level monitoring using Kalman filtering of GNSS-R data Type de document : Article/Communication Auteurs : Joakim Strandberg, Auteur ; Thomas Hobiger, Auteur ; Rüdiger Haas, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Nivellement [Termes IGN] B-Spline [Termes IGN] déformation de la croute terrestre [Termes IGN] filtre de Kalman [Termes IGN] glace de mer [Termes IGN] marée terrestre [Termes IGN] niveau de la mer [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] temps réel Résumé : (auteur) Current GNSS-R (GNSS reflectometry) techniques for sea surface measurements require data collection over longer periods, limiting their usability for real-time applications. In this work, we present a new, alternative GNSS-R approach based on the unscented Kalman filter and the so-called inverse modeling approach. The new method makes use of a mathematical description that relates SNR (signal-to-noise ratio) variations to multipath effects and uses a B-spline formalism to obtain time series of reflector height. The presented algorithm can provide results in real time with a precision that is significantly better than spectral inversion methods and almost comparable to results from inverse modeling in post-processing mode. To verify the performance, the method has been tested at station GTGU at the Onsala Space Observatory, Sweden, and at the station SPBY in Spring Bay, Australia. The RMS (root mean square) error with respect to nearby tide gauge data was found to be 2.0 cm at GTGU and 4.8 cm at SPBY when evaluating the output corresponding to real-time analysis. The method can also be applied in post-processing, resulting in RMS errors of 1.5 cm and 3.3 cm for GTGU and SPBY, respectively. Finally, based on SNR data from GTGU, it is also shown that the Kalman filter approach is able to detect the presence of sea ice with a higher temporal resolution than the previous methods and traditional remote sensing techniques which monitor ice in coastal regions. Numéro de notice : A2019-198 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0851-1 En ligne : https://doi.org/10.1007/s10291-019-0851-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92653 [article]

Decomposition of LiDAR waveforms by B-spline-based modeling / Xiang Shen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 128 (June 2017) . - pp 182 - 191 Titre : Decomposition of LiDAR waveforms by B-spline-based modeling Type de document : Article/Communication Auteurs : Xiang Shen, Auteur ; Qing-Quan Li, Auteur ; Guofeng Wu, Auteur ; Jiasong Zhu, Auteur Année de publication : 2017 Article en page(s) : pp 182 - 191 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] B-Spline [Termes IGN] décomposition de Gauss [Termes IGN] distribution, loi de [Termes IGN] forme d'onde pleine [Termes IGN] traitement du signal [Termes IGN] transformation géométrique [Termes IGN] translation Résumé : (Auteur) Waveform decomposition is a widely used technique for extracting echoes from full-waveform LiDAR data. Most previous studies recommended the Gaussian decomposition approach, which employs the Gaussian function in laser pulse modeling. As the Gaussian-shape assumption is not always satisfied for real LiDAR waveforms, some other probability distributions (e.g., the lognormal distribution, the generalized normal distribution, and the Burr distribution) have also been introduced by researchers to fit sharply-peaked and/or heavy-tailed pulses. However, these models cannot be universally used, because they are only suitable for processing the LiDAR waveforms in particular shapes. In this paper, we present a new waveform decomposition algorithm based on the B-spline modeling technique. LiDAR waveforms are not assumed to have a priori shapes but rather are modeled by B-splines, and the shape of a received waveform is treated as the mixture of finite transmitted pulses after translation and scaling transformation. The performance of the new model was tested using two full-waveform data sets acquired by a Riegl LMS-Q680i laser scanner and an Optech Aquarius laser bathymeter, comparing with three classical waveform decomposition approaches: the Gaussian, generalized normal, and lognormal distribution-based models. The experimental results show that the B-spline model performed the best in terms of waveform fitting accuracy, while the generalized normal model yielded the worst performance in the two test data sets. Riegl waveforms have nearly Gaussian pulse shapes and were well fitted by the Gaussian mixture model, while the B-spline-based modeling algorithm produced a slightly better result by further reducing 6.4% of fitting residuals, largely benefiting from alleviating the adverse impact of the ringing effect. The pulse shapes of Optech waveforms, on the other hand, are noticeably right-skewed. The Gaussian modeling results deviated significantly from original signals, and the extracted echo parameters were clearly inaccurate and unreliable. The B-spline-based method performed significantly better than the Gaussian and lognormal models by reducing 45.5% and 11.5% of their fitting errors, respectively. Much more precise echo properties can accordingly be retrieved with a high probability. Benefiting from the flexibility of B-splines on fitting arbitrary curves, the new method has the potentiality for accurately modeling various full-waveform LiDAR data, whether they are nearly Gaussian or non-Gaussian in shape. Numéro de notice : A2017-334 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.03.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.03.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85487 [article]

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