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A Powerful Correspondence Selection Method for Point Cloud Registration Based on Machine Learning / Wuyong Tao in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 11 (November 2023)
[article]
Titre : A Powerful Correspondence Selection Method for Point Cloud Registration Based on Machine Learning Type de document : Article/Communication Auteurs : Wuyong Tao, Auteur ; Dong Xu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 703 - 712 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de points
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] semis de pointsRésumé : (auteur) Correspondence selection is an indispensable process in point cloud registration. The success of point cloud registration largely depends on a good correspondence selection method. For this purpose, a novel correspondence selection method is proposed in this paper. First, two geometric constraints, one of which is proposed in this paper, are used to compute the compatibility score between two correspondences. Then, the feature vectors of the correspondences are constructed according to the compatibility scores between the correspondence and others. A support vector machine classifier is trained to classify the correct and incorrect correspondences by using the feature vectors. The experimental results demonstrate that our method can choose the right correspondences well and get high precision and F-score performance. Also, our method has the best robustness to noise, pointdensity variation, and partial overlap compared to the other methods. Numéro de notice : A2023-237 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.23-00046R2 En ligne : https://doi.org/10.14358/PERS.23-00046R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103597
in Photogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 11 (November 2023) . - pp 703 - 712[article]A hierarchical multiview registration framework of TLS point clouds based on loop constraint / Hao Wu in ISPRS Journal of photogrammetry and remote sensing, vol 195 (January 2023)
[article]
Titre : A hierarchical multiview registration framework of TLS point clouds based on loop constraint Type de document : Article/Communication Auteurs : Hao Wu, Auteur ; Li Yan, Auteur ; Hong Xie, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 65 - 76 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] appariement de points
[Termes IGN] approche hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] graphe
[Termes IGN] recalage d'image
[Termes IGN] semis de points
[Termes IGN] superposition de données
[Termes IGN] traitement de semis de pointsRésumé : (auteur) Automatic registration of multiple point clouds is a significant preprocessing step for 3D computer vision tasks including semantic segmentation, 3D modelling, change detection, etc. Many methods were proposed to deal with this problem and yet most of them are not fully utilizing the redundant information offered by multiple common overlaps among point clouds. The existing methods are also inefficient when dealing with large-scale point clouds. In this paper, a novel automatic registration framework is presented to align point clouds efficiently and robustly. First, the overall number of scans is grouped into several scan-blocks by a proposed blocking strategy, and we build the pairwise relationship among scans through a fully connected graph in each scan-block. Second, perform loop-based coarse registration in each scan-block using a proposed false matches removal strategy. The proposed strategy can effectively identify grossly wrong scan-to-scan matches. Third, the minimum spanning tree is extracted from the graph, and ICP is applied along its edges. Moreover, the Lu–Milios algorithm is used to further optimize all poses at once by utilizing all redundant information in each scan-block. Finally, global block-to-block registration aligns all scan-blocks into a uniform coordinate reference. We test our framework on challenging WHU-TLS datasets, ETH datasets, and Robotic 3D Scan datasets to evaluate the efficiency, accuracy, as well as robustness. The experiment results show that our method achieves the state-of-the-art accuracy, while the time performance is improved by more than 30% compared with the state-of-the-art algorithms. Our source code is made available at https://github.com/WuHao-WHU/HL-MRF for benchmarking purposes. Numéro de notice : A2023-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.11.004 Date de publication en ligne : 19/11/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.11.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102112
in ISPRS Journal of photogrammetry and remote sensing > vol 195 (January 2023) . - pp 65 - 76[article]Automatic registration method of multi-source point clouds based on building facades matching in urban scenes / Yumin Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 12 (December 2022)
[article]
Titre : Automatic registration method of multi-source point clouds based on building facades matching in urban scenes Type de document : Article/Communication Auteurs : Yumin Tan, Auteur ; Yanzhe Shi, Auteur ; Yunxin Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 767 - 782 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] algorithme ICP
[Termes IGN] appariement de formes
[Termes IGN] appariement de points
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] façade
[Termes IGN] fusion de données multisource
[Termes IGN] modélisation 3D
[Termes IGN] photogrammétrie aérienne
[Termes IGN] points registration
[Termes IGN] Ransac (algorithme)
[Termes IGN] recalage de données localisées
[Termes IGN] scène urbaine
[Termes IGN] superposition de donnéesRésumé : (auteur) Both UAV photogrammetry and lidar have become common in deriv- ing three-dimensional models of urban scenes, and each has its own advantages and disadvantages. However, the fusion of these multisource data is still challenging, in which registration is one of the most important stages. In this paper, we propose a method of coarse point cloud registration which consists of two steps. The first step is to extract urban building facades in both an oblique photogrammetric point cloud and a lidar point cloud. The second step is to align the two point clouds using the extracted building facades. Object Vicinity Distribution Feature (Dijkman and Van Den Heuvel 2002) is introduced to describe the distribution of building facades and register the two heterologous point clouds. This method provides a good initial state for later refined registration process and is translation, rotation, and scale invariant. Experiment results show that the accuracy of this proposed automatic registration method is equiva- lent to the accuracy of manual registration with control points. Numéro de notice : A2022-882 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.22-00069R3 Date de publication en ligne : 01/12/2022 En ligne : https://doi.org/10.14358/PERS.22-00069R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102206
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 12 (December 2022) . - pp 767 - 782[article]Lidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks / Aurélien Brun in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)
[article]
Titre : Lidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks Type de document : Article/Communication Auteurs : Aurélien Brun, Auteur ; Davide Antonio Cucci, Auteur ; Jan Skaloud, Auteur Année de publication : 2022 Article en page(s) : pp 185 - 200 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] appariement de points
[Termes IGN] centrale inertielle
[Termes IGN] données lidar
[Termes IGN] filtre de Kalman
[Termes IGN] géoréférencement
[Termes IGN] précision du positionnement
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de points
[Termes IGN] signal GNSS
[Termes IGN] superpositionRésumé : (auteur) With the objective of improving the registration of lidar point clouds produced by kinematic scanning systems, we propose a novel trajectory adjustment procedure that leverages on the automated extraction of selected reliable 3D point–to–point correspondences between overlapping point clouds and their joint integration (adjustment) together with raw inertial and GNSS observations. This is performed in a tightly coupled fashion using a dynamic network approach that results in an optimally compensated trajectory through modeling of errors at the sensor, rather than the trajectory, level. The 3D correspondences are formulated as static conditions within the dynamic network and the registered point cloud is generated with significantly higher accuracy based on the corrected trajectory and possibly other parameters determined within the adjustment. We first describe the method for selecting correspondences and how they are inserted into the dynamic network via new observation model while providing an open-source implementation of the solver employed in this work. We then describe the experiments conducted to evaluate the performance of the proposed framework in practical airborne laser scanning scenarios with low-cost MEMS inertial sensors. In the conducted experiments, the method proposed to establish 3D correspondences is effective in determining point–to–point matches across a wide range of geometries such as trees, buildings and cars. Our results demonstrate that the method improves the point cloud registration accuracy (5 in nominal and 10 in emulated GNSS outage conditions within the studied cases), which is otherwise strongly affected by errors in the determined platform attitude or position, and possibly determine unknown boresight angles. The proposed methods remain effective even if only a fraction (0.1%) of the total number of established 3D correspondences are considered in the adjustment. Numéro de notice : A2022-413 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.04.027 Date de publication en ligne : 19/05/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.04.027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100764
in ISPRS Journal of photogrammetry and remote sensing > vol 189 (July 2022) . - pp 185 - 200[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022071 SL Revue Centre de documentation Revues en salle Disponible Automatic registration of mobile mapping system Lidar points and panoramic-image sequences by relative orientation model / Ningning Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 12 (December 2021)
[article]
Titre : Automatic registration of mobile mapping system Lidar points and panoramic-image sequences by relative orientation model Type de document : Article/Communication Auteurs : Ningning Zhu, Auteur ; Bisheng Yang, Auteur ; Zhen Dong, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 913 - 922 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 de traits caractéristiques
[Termes IGN] image panoramique
[Termes IGN] modèle géométrique de prise de vue
[Termes IGN] orientation relative
[Termes IGN] scène urbaine
[Termes IGN] semis de points
[Termes IGN] séquence d'images
[Termes IGN] superposition de données
[Termes IGN] SURF (algorithme)Résumé : (Auteur) To register mobile mapping system (MMS) lidar points and panoramic-image sequences, a relative orientation model of panoramic images (PROM) is proposed. The PROM is suitable for cases in which attitude or orientation parameters are unknown in the panoramic-image sequence. First, feature points are extracted and matched from panoramic-image pairs using the SURF algorithm. Second, these matched feature points are used to solve the relative attitude parameters in the PROM. Then, combining the PROM with the absolute position and attitude parameters of the initial panoramic image, the MMS lidar points and panoramic-image sequence are registered. Finally, the registration accuracy of the PROM method is assessed using corresponding points manually selected from the MMS lidar points and panoramic-image sequence. The results show that three types of MMS data sources are registered accurately based on the proposed registration method. Our method transforms the registration of panoramic images and lidar points into image feature-point matching, which is suitable for diverse road scenes compared with existing methods. Numéro de notice : A2021-899 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00006R2 Date de publication en ligne : 01/12/2021 En ligne : https://doi.org/10.14358/PERS.21-00006R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99298
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 12 (December 2021) . - pp 913 - 922[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021121 SL Revue Centre de documentation Revues en salle Disponible Enhanced trajectory estimation of mobile laser scanners using aerial images / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)PermalinkGuided feature matching for multi-epoch historical image blocks pose estimation / Lulin Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkLeveraging photogrammetric mesh models for aerial-ground feature point matching toward integrated 3D reconstruction / Qing Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkSemiautomatically register MMS LiDAR points and panoramic image sequence using road lamp and lane / Ningning Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 11 (November 2019)PermalinkReview of mobile laser scanning target‐free registration methods for urban areas using improved error metrics / Hoang Long Nguyen in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkAutomatic 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)PermalinkPermalinkGraph-based matching of points-of-interest from collaborative geo-datasets / Tessio Novack in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkNew point matching algorithm using sparse representation of image patch feature for SAR image registration / Jianwei Fan in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkImproving FOSS photogrammetric workflows for processing large image datasets / Oscar Martinez-Rubi in Open Geospatial Data, Software and Standards, vol 2 (2017)PermalinkSkeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images / Zhihua Xua in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)PermalinkAutomatic extraction of road networks from GPS traces / Jia Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)PermalinkA manifold alignment approach for hyperspectral image visualization with natural color / Danping Liao in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkLaser ranging plus GNSS / Jyh-Ching Juang in GPS world, vol 27 n° 5 (May 2016)PermalinkAcquisition et reconstruction de données 3D denses sous-marines en eau peu profonde par des robots d'exploration / Loïca Avanthey (2016)PermalinkAn approach to fine coregistration between very high resolution multispectral images based on registration noise distribution / Youkyung Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkImproved nonsubsampled contourlet transform for multi-sensor image registration / R. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 1 (January 2013)PermalinkMise en correspondance de points 3D obtenus avec une grande "base-line" / Narut Soontranon (Juin 2013)PermalinkA simple and robust feature point matching algorithm based on restricted spatial order constraints for aerial image registration / Z. Liu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkInterest operators for feature-based matching in close range photogrammetry / I. Jazayeri in Photogrammetric record, vol 25 n° 129 (March - May 2010)PermalinkAutomatically and accurately conflating raster maps with orthoimagery / C.C. Chen in Geoinformatica, vol 12 n° 3 (September - November 2008)Permalink