Centre de documentation
scientifique

Semantic segmentation of bridge components and road infrastructure from mobile LiDAR data / Yi-Chun Lin in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)  

Public [article]  inISPRS Open Journal of Photogrammetry and Remote Sensing > vol 6 (December 2022) . - n° 100023 Titre : Semantic segmentation of bridge components and road infrastructure from mobile LiDAR data Type de document : Article/Communication Auteurs : Yi-Chun Lin, Auteur ; Ayman Habib, Auteur Année de publication : 2022 Article en page(s) : n° 100023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage profond [Termes IGN] autoroute [Termes IGN] couplage GNSS-INS [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] lidar mobile [Termes IGN] pont [Termes IGN] réseau neuronal de graphes [Termes IGN] réseau routier [Termes IGN] segmentation sémantique [Termes IGN] semis de points Résumé : (auteur) Emerging mobile LiDAR mapping systems exhibit great potential as an alternative for mapping urban environments. Such systems can acquire high-quality, dense point clouds that capture detailed information over an area of interest through efficient field surveys. However, automatically recognizing and semantically segmenting different components from the point clouds with efficiency and high accuracy remains a challenge. Towards this end, this study proposes a semantic segmentation framework to simultaneously classify bridge components and road infrastructure using mobile LiDAR point clouds while providing the following contributions: 1) a deep learning approach exploiting graph convolutions is adopted for point cloud semantic segmentation; 2) cross-labeling and transfer learning techniques are developed to reduce the need for manual annotation; and 3) geometric quality control strategies are proposed to refine the semantic segmentation results. The proposed framework is evaluated using data from two mobile mapping systems along an interstate highway with 27 highway bridges. With the help of the proposed cross-labeling and transfer learning strategies, the deep learning model achieves an overall accuracy of 84% using limited training data. Moreover, the effectiveness of the proposed framework is verified through test covering approximately 42 miles along the interstate highway, where substantial improvement after quality control can be observed. Numéro de notice : A2022-814 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.ophoto.2022.100023 Date de publication en ligne : 24/10/2022 En ligne : https://doi.org/10.1016/j.ophoto.2022.100023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101975 [article]

Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 717 - 733 Titre : Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing Type de document : Article/Communication Auteurs : Radhika Ravi, Auteur ; Ayman Habib, Auteur Année de publication : 2021 Article en page(s) : pp 717 - 733 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] alignement des données [Termes IGN] chevauchement [Termes IGN] compensation par moindres carrés [Termes IGN] données lidar [Termes IGN] lidar mobile [Termes IGN] matrice [Termes IGN] matrice de covariance [Termes IGN] modèle de Gauss-Helmert [Termes IGN] modèle de Gauss-Markov [Termes IGN] modèle mathématique [Termes IGN] modélisation 3D [Termes IGN] pondération [Termes IGN] semis de points Résumé : (Auteur) This article proposes a solution to special least squares adjustment (LSA) models with a rank-deficient weight matrix, which are commonly encountered in geomatics. The two sources of rank deficiency in weight matrices are discussed: naturally occurring due to the inherent characteristics of LSA mathematical models and artificially induced to eliminate nuisance parameters from LSA estimation. The physical interpretation of the sources of rank deficiency is demonstrated using a case study to solve the problem of 3D line fitting, which is often encountered in geomatics but has not been addressed fully to date. Finally, some geomatics-related applications—mobile lidar system calibration, point cloud registration, and single-photo resection—are discussed along with respective experimental results, to emphasize the need to assess LSA models and their weight matrices to draw inferences regarding the effective contribution of observations. The discussion and results demonstrate the vast applications of this research in geomatics as well as other engineering domains. Numéro de notice : A2021-675 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00081R3 Date de publication en ligne : 10/01/2021 En ligne : https://doi.org/10.14358/PERS.20-00081R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98861 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2021101	SL	Revue	Centre de documentation	Revues en salle	Disponible

Three-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint / Fangning He in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 278 - 291 Titre : Three-point-based solution for automated motion parameter estimation of a multi-camera indoor mapping system with planar motion constraint Type de document : Article/Communication Auteurs : Fangning He, Auteur ; Ayman Habib, Auteur Année de publication : 2018 Article en page(s) : pp 278 - 291 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] appariement d'images [Termes IGN] carte d'intérieur [Termes IGN] compensation par faisceaux [Termes IGN] coplanarité [Termes IGN] élément d'orientation interne [Termes IGN] modélisation 3D [Termes IGN] orientation relative [Termes IGN] Ransac (algorithme) [Termes IGN] reconstruction 3D [Termes IGN] structure-from-motion [Termes IGN] valeur aberrante Résumé : (auteur) Accurate indoor 3D models have become a key prerequisite for various applications. Through state-of-the-art image processing techniques, 3D models can be generated from high quality images captured by off-the-shelf digital cameras. To acquire redundant data and produce real scale models, a multi-camera system can be used. However, dedicated approaches for image-based 3D reconstruction using mapping platforms equipped with multiple cameras have not been fully addressed. Assuming the availability of prior information regarding the platform trajectory, this paper presents a new approach for reliable estimation of system motion parameters between different data acquisition epochs of a multi-camera system. This approach, which assumes planar motion of the utilized platform, provides a three-point closed-form solution. The derived solutions are then incorporated within a modified RANSAC framework for outlier detection/removal. It is worth noting that, different from the existing General Camera Model (GCM)-based solutions, the proposed approach is based on a modified co-planarity model, which is essentially a direct extension of the classic stereo-based relative orientation. Moreover, since the proposed approach only provides a maximum number of four possible solutions for system motion parameters over different epochs, it has better computational efficiency when compared to other existing algorithms. Experimental results from real datasets acquired with different configurations have demonstrated the reliability of the proposed approach in motion parameter estimation for indoor multi-camera mapping systems. Numéro de notice : A2018-297 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.011 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.011 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90417 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Multi-dimensional and multi-temporal motion estimation of a beam surface during dynamic testing using low-frame rate digital cameras / I. Detchev in Applied geomatics, vol 9 n° 3 (September 2017)  

Public [article]  inApplied geomatics > vol 9 n° 3 (September 2017) . - pp 127 - 141 Titre : Multi-dimensional and multi-temporal motion estimation of a beam surface during dynamic testing using low-frame rate digital cameras Type de document : Article/Communication Auteurs : I. Detchev, Auteur ; Derek Litchi, Auteur ; Ayman Habib, Auteur ; Mamdouh El-Badry, Auteur Année de publication : 2017 Article en page(s) : pp 127 - 141 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] ajustement de paramètres [Termes IGN] caméra numérique [Termes IGN] déviation de la verticale [Termes IGN] méthode des moindres carrés [Termes IGN] photogrammétrie métrologique Résumé : (Auteur) The combination of digital close-range photogrammetric systems and image processing techniques has been employed in structural health monitoring applications for more than 10 years. The use of off-the-shelf entry level digital single-lens reflex cameras has lately become a suitable choice even for applications requiring sub-millimetre- level precision especially when the involved devices need to be inexpensive. The drawback of such low-cost cameras is in the trade-off between spatial resolution, frame rate, and burst rate—at the highest available spatial resolution, a high frame rate is either not possible or it has a low burst rate. This may be problematic when monitoring a structural component during a dynamic/fatigue test. In order to estimate specimen motion in such a situation, this paper proposes an innovative sinusoidal fitting based on a least squares adjustment. This method simultaneously processes multiple bursts of data in order to synthetically increase the sampling frequency of the system. The input data for the adjustment comes from a full surface modelling procedure based on a newly proposed generalized 3D polynomial. The experimental results include a beam deformation test performed in a structures laboratory. The new sinusoidal fitting method effectively increased the system temporal resolution three-fold, which improved the precision of the derived parameters with up to two orders of magnitude. The root mean square error of the residuals were as good as 26 μm, and the one of the estimated amplitudes from the photogrammetric system versus a set of laser transducers used as control was as small as 43 μm. Numéro de notice : A2017-595 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-017-0184-0 Date de publication en ligne : 10/04/2017 En ligne : https://doi.org/10.1007/s12518-017-0184-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86803 [article]

Planar-based adaptive down-sampling of point clouds / Yun-Jou Lin in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 12 (December 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 12 (December 2016) . - pp 955 - 966 Titre : Planar-based adaptive down-sampling of point clouds Type de document : Article/Communication Auteurs : Yun-Jou Lin, Auteur ; Ronald R Benziger, Auteur ; Ayman Habib, Auteur Année de publication : 2016 Article en page(s) : pp 955 - 966 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] densité des points [Termes IGN] segmentation [Termes IGN] semis de points [Termes IGN] surface plane [Termes IGN] traitement automatique de données [Termes IGN] traitement de données localisées Résumé : (auteur) Derived point clouds from laser scanners and image-based dense-matching techniques usually include tremendous number of points. Processing (e.g., segmenting) such huge dataset is time-consuming and might not be necessary. For example, a planar surface just needs few points to be defined. In contrast, linear/cylindrical and rough features require more points for reliable modeling since during the data acquisition process, only a portion of linear/cylindrical features is present in the point cloud. This paper introduces an adaptive down-sampling strategy for removing redundant points from high density planar regions while retaining points in planar areas with sparse points and all the points within linear/cylindrical and rough neighborhoods. To demonstrate the feasibility and performance of the proposed procedure, a comparison of segmentation results using original laser and image-based point clouds as well as the adaptively, uniformly, and point-spacing-based down-sampled point clouds are presented while commenting on the computational efficiency and the segmentation quality. Numéro de notice : A2016-984 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.12.955 En ligne : https://doi.org/10.14358/PERS.82.12.955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83700 [article]

Quaternion-based solutions for the single photo resection problem / Mehdi Mazaheri in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 3 (March 2015)  

Permalink

Association-matrix-based sample consensus approach for automated registration of terrestrial laser scans using linear features / Kaleel Al-Durgham in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 11 (November 2014)  

Permalink

Automatic representation and reconstruction of DBM from LiDAR data using Recursive Minimum Bounding Rectangle / Eunju Kwak in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)  

Permalink