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Automatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 41 - 58 Titre : Automatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery Type de document : Article/Communication Auteurs : Zille Hussnain, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur ; M. George Vosselman, Auteur Année de publication : 2019 Article en page(s) : pp 41 - 58 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] appariement de points [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] point de liaison (imagerie) [Termes descripteurs IGN] Rotterdam [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] télémétrie laser mobile Résumé : (Auteur) Poor GNSS measurements in urban areas caused by blocked GNSS signals and multi-path is a well-known problem, which leads to an inaccurate trajectory estimation of Mobile Laser Scanning (MLS) platforms. Consequently, the MLS point cloud contains positioning errors. This paper presents a new method for the automatic extraction of accurate 3D tie points for the trajectory adjustment of MLS platforms in GNSS denied or troubled areas. The new method relies on aerial imagery as a reliable external source of reference provided that accurate exterior orientation parameters are available. Accordingly, one of the main objectives is to register the mobile laser scanning point cloud with corresponding aerial images. The matches between aerial images are used to obtain 3D tie points by forward intersection. By also determining the corresponding locations in the point cloud we obtain a 3D-3D correspondence between the MLS point cloud and the aerial images. In the future, the obtained 3D-3D correspondences will be used for trajectory adjustment. Our automatic tie point extraction procedure is tested on two independent MLS point clouds. The point clouds were acquired by two different platforms in Rotterdam. The aerial imagery of the same area was acquired at a different time. We evaluated the matching results for both datasets and concluded that the new procedure reliably extracted the 3D tie points for 55% of the tiles of the size of 90 m from the first MLS dataset. In the second dataset, 60% of the tiles of size 74 m yielded reliable 3D tie points. It is not necessary to successfully register all tiles because the results of this work will be used for the trajectory adjustment and the IMU can reliably support the positioning for small intervals. Numéro de notice : A2019-263 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.010 date de publication en ligne : 04/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93076 [article]

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Discriminative-dictionary-learning-based multilevel point-cluster features for ALS point-cloud classification / Zhenxin Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 12 (December 2016) . - pp 7309 - 7322 Titre : Discriminative-dictionary-learning-based multilevel point-cluster features for ALS point-cloud classification Type de document : Article/Communication Auteurs : Zhenxin Zhang, Auteur ; Liqiang Zhang, Auteur ; Xiaohua Tong, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 7309 - 7322 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] classificateur [Termes descripteurs IGN] codage [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] problème de Dirichlet Résumé : (Auteur) Efficient presentation and recognition of on-ground objects from airborne laser scanning (ALS) point clouds are a challenging task. In this paper, we propose an approach that combines a discriminative-dictionary-learning-based sparse coding and latent Dirichlet allocation (LDA) to generate multilevel point-cluster features for ALS point-cloud classification. Our method takes advantage of the labels of training data and each dictionary item to enforce discriminability in sparse coding during the dictionary learning process and more accurately further represent point-cluster features. The multipath AdaBoost classifiers with the hierarchical point-cluster features are trained, and we apply them to the classification of unknown points by the heritance of the recognition results under different paths. Experiments are performed on different ALS point clouds; the experimental results have shown that the extracted point-cluster features combined with the multipath classifiers can significantly enhance the classification accuracy, and they have demonstrated the superior performance of our method over other techniques in point-cloud classification. Numéro de notice : A2016-931 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2599163 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83345 [article]

Robust locally weighted regression techniques for ground surface points filtering in mobile laser scanning three dimensional point cloud data / Abdul Nurunnabi in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 2181 - 2193 Titre : Robust locally weighted regression techniques for ground surface points filtering in mobile laser scanning three dimensional point cloud data Type de document : Article/Communication Auteurs : Abdul Nurunnabi, Auteur ; Geoff West, Auteur ; David Belton, Auteur Année de publication : 2016 Article en page(s) : pp 2181 - 2193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] ajustement de paramètres [Termes descripteurs IGN] algorithme de filtrage [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] analyse de données [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] régression [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] télémétrie laser mobile [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) This paper introduces robust algorithms for extracting the ground points in laser scanning 3-D point cloud data. Global polynomial functions have been used for filtering algorithms for point cloud data; however, it is not suitable as it may lead to bias for the filtering algorithms and can cause misclassification errors when many different objects are present. In this paper, robust statistical approaches are coupled with locally weighted 2-D regression that fits without any predefined global function for the variables of interest. Algorithms are performed iteratively on 2-D profiles: x - z and y - z. The z (elevation) values are robustly down weighted based on the residuals for the fitted points. The new set of down-weighted z values, along with the corresponding x (or y) values, is used to get a new fit for the lower surface level. The process of fitting and down weighting continues until the difference between two consecutive fits is insignificant. The final fit is the required ground level, and the ground surface points are those that fall within the ground level and the level after adding some threshold value with the ground level for z values. Experimental results are compared with the recently proposed segmentation method through simulated and real mobile laser scanning point clouds from urban areas that include many objects that appear in road scenes such as short walls, large buildings, electric poles, signposts, and cars. Results show that the proposed robust methods efficiently extract ground surface points with better than 97% accuracy. Numéro de notice : A2016-840 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2015.2496972 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82884 [article]

Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3 (September 2014)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > II-3 (September 2014) . - pp 181 - 188 Titre : Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Boris Jutzi, Auteur ; Clément Mallet , Auteur Congrès : PCV 2014, ISPRS Technical Commission 3 Symposium Photogrammetric Computer vision (5 - 7 septembre 2014; Zurich, Suisse), Commanditaire Année de publication : 2014 Article en page(s) : pp 181 - 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse d'image numérique [Termes descripteurs IGN] classification [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] semis de points Résumé : (auteur) 3D scene analysis by automatically assigning 3D points a semantic label has become an issue of major interest in recent years. Whereas the tasks of feature extraction and classification have been in the focus of research, the idea of using only relevant and more distinctive features extracted from optimal 3D neighborhoods has only rarely been addressed in 3D lidar data processing. In this paper, we focus on the interleaved issue of extracting relevant, but not redundant features and increasing their distinctiveness by considering the respective optimal 3D neighborhood of each individual 3D point. We present a new, fully automatic and versatile framework consisting of four successive steps: (i) optimal neighborhood size selection, (ii) feature extraction, (iii) feature selection, and (iv) classification. In a detailed evaluation which involves 5 different neighborhood definitions, 21 features, 6 approaches for feature subset selection and 2 different classifiers, we demonstrate that optimal neighborhoods for individual 3D points significantly improve the results of scene interpretation and that the selection of adequate feature subsets may even further increase the quality of the derived results. Numéro de notice : A2014-799 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-181-2014 date de publication en ligne : 07/08/2014 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-181-2014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82699 [article]

SIFT (Scale Invariant Feature Transform) : Un outil pour la mise en correspondance d’images / Arnaud Le Bris (2008)

Public contenu dans Journées de la Recherche IGN 2008 / Journées Recherche de l'IGN 2008 (11 mars 2008; Saint-Mandé, France) (2008)   Titre : SIFT (Scale Invariant Feature Transform) : Un outil pour la mise en correspondance d’images Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur Congrès : Journées Recherche de l'IGN 2008 (11 mars 2008; Saint-Mandé, France), Commanditaire Editeur : Saint-Mandé : Institut Géographique National - IGN Année de publication : 2008 Importance : 63 p. Format : 21 x 30 cm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] aérotriangulation [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] extraction de points [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image oblique [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] point de liaison (imagerie) [Termes descripteurs IGN] points homologues [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] recalage d'image [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] Stéréopolis [Termes descripteurs IGN] tableau d'assemblage Numéro de notice : C2008-017 Thématique : IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90972