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Enhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 173 (March 2021) . - pp 66 - 78 Titre : Enhanced trajectory estimation of mobile laser scanners using aerial images Type de document : Article/Communication Auteurs : Zille Hussnain, Auteur ; Sander J. Oude Elberink, Auteur ; M. George Vosselman, Auteur Année de publication : 2021 Article en page(s) : pp 66 - 78 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] appariement de points [Termes IGN] atténuation du signal [Termes IGN] balayage laser [Termes IGN] canyon urbain [Termes IGN] centrale inertielle [Termes IGN] données lidar [Termes IGN] erreur [Termes IGN] image captée par drone [Termes IGN] mesurage par GNSS [Termes IGN] semis de points [Termes IGN] trajectoire [Termes IGN] trajet multiple Résumé : (auteur) Multipath effects and signal obstruction by buildings in urban canyons can lead to inaccurate GNSS measurements and therefore errors in the estimated trajectory of Mobile Laser Scanning (MLS) systems; consequently, derived point clouds are distorted and lose spatial consistency. We obtain decimetre-level trajectory accuracy making use of corresponding points between the MLS data and aerial images with accurate exterior orientations instead of using ground control points. The MLS trajectory is estimated based on observation equations resulting from these corresponding points, the original IMU observations, and soft constraints on the pitch and yaw rotations of the vehicle. We analyse the quality of the trajectory enhancement under several conditions where the experiments were designed to test the influence of the number and quality of corresponding points and to test different settings for a B-spline representation of the vehicle trajectory. The method was tested on two independently acquired MLS datasets in Rotterdam by enhancing the trajectories and evaluating them using checkpoints. The RMSE values of the original GNSS/IMU based Kalman filter results at the checkpoints were 0.26 m, 0.30 m, and 0.47 m for the X-, Y- and Z-coordinates in the first dataset and 1.10 m, 1.51 m, and 1.81 m in the second dataset. The latter dataset was recorded with a lower quality IMU in an area with taller buildings. After trajectory adjustment these RMSE values were reduced to 0.09 m, 0.11 m, and 0.16 m for the first dataset and 0.12 m, 0.14 m, and 0.18 m for the second dataset. The results confirmed that, if sufficient tie points between the point cloud and aerial imagery are available, the method supports geo-referencing of MLS point clouds in urban canyons with a near-decimetre accuracy. Numéro de notice : A2021-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.005 Date de publication en ligne : 17/01/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.005 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96877 [article]

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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 IGN] appariement de points [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] extraction automatique [Termes IGN] extraction de points [Termes IGN] image aérienne [Termes IGN] point de liaison (imagerie) [Termes IGN] Rotterdam (Pays-Bas) [Termes IGN] télémètre laser terrestre [Termes 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 Affiliation des auteurs : non IGN 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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Semantic segmentation of road furniture in mobile laser scanning data / Fashuai Li 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 98 - 113 Titre : Semantic segmentation of road furniture in mobile laser scanning data Type de document : Article/Communication Auteurs : Fashuai Li, Auteur ; Matti Lehtomäki, Auteur ; Sander J. Oude Elberink, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 98 - 113 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] classification bayesienne [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] mobilier urbain [Termes IGN] segmentation sémantique Résumé : (Auteur) Road furniture recognition has become a prevalent issue in the past few years because of its great importance in smart cities and autonomous driving. Previous research has especially focussed on pole-like road furniture, such as traffic signs and lamp posts. Published methods have mainly classified road furniture as individual objects. However, most road furniture consists of a combination of classes, such as a traffic sign mounted on a street light pole. To tackle this problem, we propose a framework to interpret road furniture at a more detailed level. Instead of being interpreted as single objects, mobile laser scanning data of road furniture is decomposed in elements individually labelled as poles, and objects attached to them, such as, street lights, traffic signs and traffic lights. In our framework, we first detect road furniture from unorganised mobile laser scanning point clouds. Then detected road furniture is decomposed into poles and attachments (e.g. traffic signs). In the interpretation stage, we extract a set of features to classify the attachments by utilising a knowledge-driven method and four representative types of machine learning classifiers, which are random forest, support vector machine, Gaussian mixture model and naïve Bayes, to explore the optimal method. The designed features are the unary features of attachments and the spatial relations between poles and their attachments. Two experimental test sites in Enschede dataset and Saunalahti dataset were applied, and Saunalahti dataset was collected in two different epochs. In the experimental results, the random forest classifier outperforms the other methods, and the overall accuracy acquired is higher than 80% in Enschede test site and higher than 90% in both Saunalahti epochs. The designed features play an important role in the interpretation of road furniture. The results of two epochs in the same area prove the high reliability of our framework and demonstrate that our method achieves good transferability with an accuracy over 90% through employing the training data of one epoch to test the data in another epoch. Numéro de notice : A2019-266 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.06.001 Date de publication en ligne : 08/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.001 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93081 [article]

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Object-based classification of terrestrial laser scanning point clouds for landslide monitoring / Andreas Mayr in Photogrammetric record, vol 32 n° 160 (December 2017)  

Public [article]  inPhotogrammetric record > vol 32 n° 160 (December 2017) . - pp 377 - 397 Titre : Object-based classification of terrestrial laser scanning point clouds for landslide monitoring Type de document : Article/Communication Auteurs : Andreas Mayr, Auteur ; Martin Rutzinger, Auteur ; Magnus Bremer, Auteur ; Sander J. Oude Elberink, Auteur ; Felix Stumpf, Auteur ; Clemens Geitner, Auteur Année de publication : 2017 Conférence : VGC 2016, 2nd virtual geoscience conference 22/09/2016 23/09/2016 Bergen Norvège Proceedings Wiley Article en page(s) : pp 377 - 397 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage automatique [Termes IGN] classification orientée objet [Termes IGN] compréhension de l'image [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] effondrement de terrain [Termes IGN] relation topologique 3D [Termes IGN] surveillance géologique Résumé : (auteur) Terrestrial laser scanning (TLS) is often used to monitor landslides and other gravitational mass movements with high levels of geometric detail and accuracy. However, unstructured TLS point clouds lack semantic information, which is required to geomorphologically interpret the measured changes. Extracting meaningful objects in a complex and dynamic environment is challenging due to the objects' fuzziness in reality, as well as the variability and ambiguity of their patterns in a morphometric feature space. This work presents a point‐cloud‐based approach for classifying multitemporal scenes of a hillslope affected by shallow landslides. The 3D point clouds are segmented into morphologically homogeneous and spatially connected parts. These segments are classified into seven target classes (scarp, eroded area, deposit, rock outcrop and different classes of vegetation) in a two‐step procedure: a supervised classification step with a machine‐learning classifier using morphometric features, followed by a correction step based on topological rules. This improves the final object extraction considerably. Numéro de notice : A2017-899 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12215 Date de publication en ligne : 13/12/2017 En ligne : https://doi.org/10.1111/phor.12215 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89522 [article]

III-3 - July 2016 - [actes] XXIII ISPRS Congress, Commission III, 12–19 July 2016, Prague, Czech Republic (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Lena Halounova  

Public [n° ou bulletin]  est un bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences / International society for photogrammetry and remote sensing (2012 - )   Titre : III-3 - July 2016 - [actes] XXIII ISPRS Congress, Commission III, 12–19 July 2016, Prague, Czech Republic Type de document : Périodique Auteurs : Lena Halounova, Éditeur scientifique ; Konrad Schindler, Éditeur scientifique ; A. Limpouch, Éditeur scientifique ; T. Pajdla, Éditeur scientifique ; V. Safar, Éditeur scientifique ; H. Mayer, Éditeur scientifique ; Sander J. Oude Elberink, Éditeur scientifique ; Clément Mallet , Éditeur scientifique ; Franz Rottensteiner, Éditeur scientifique ; Mathieu Brédif , Éditeur scientifique ; Jan Skaloud, Éditeur scientifique ; Uwe Stilla, Éditeur scientifique Congrès : ISPRS 2016, 23th international congress (12 - 19 juillet 2016; Prague, République tchèque), Auteur Année de publication : 2016 Langues : Français (fre) Numéro de notice : sans Affiliation des auteurs : IGN+Ext (2012-2019) Nature : Numéro de périodique nature-HAL : DirectOuvrColl/Actes DOI : sans Date de publication en ligne : 02/06/2016 En ligne : http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-3/index.html Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=bulletin_display&id=27482 [n° ou bulletin]

Contient

• Simultaneous detection and tracking of pedestrian from panoramic laser scanning data / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, III-3 (July 2016)  
• Fusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, III-3 (July 2016)    

23th ISPRS international congress, 3. Commission III / Lena Halounova (2016)  

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II-3 W5 - October 2015 - [actes] ISPRS Geospatial Week 2015, 28 September–3 October 2015, La Grande Motte, France (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Clément Mallet  

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Flexible building primitives for 3D building modeling / B. Xiong in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)  

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ISPRS Geospatial Week 2015 / Clément Mallet (2015)  

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A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds / B. Xiong in ISPRS Journal of photogrammetry and remote sensing, vol 93 (July 2014)

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Multiple-entity based classification of airborne laser scanning data in urban areas / S. Xu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)

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II-5 W2 - November 2013 - [actes] ISPRS Workshop Laser Scanning 2013, 11–13 November 2013, Antalya, Turkey (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / Marco Scaioni  

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EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning / Harri Kaartinen (2013)

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Recognizing basic structures from mobile laser scanning data for road inventory studies / Shi Pu in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 6 supplement (December 2011)  

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Acquisition of 3D topography / Sander J. Oude Elberink (2010)  

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