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Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods / Ferdinand Maiwald in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 748 Titre : Fully automated pose estimation of historical images in the context of 4D geographic information systems utilizing machine learning methods Type de document : Article/Communication Auteurs : Ferdinand Maiwald, Auteur ; Christoph Lehmann, Auteur ; Taras Lazariv, Auteur Année de publication : 2021 Article en page(s) : n° 748 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] apprentissage automatique [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] échelle de temps [Termes IGN] estimation de pose [Termes IGN] image ancienne [Termes IGN] image terrestre [Termes IGN] métadonnées [Termes IGN] modélisation 4D [Termes IGN] patrimoine culturel [Termes IGN] recherche d'image basée sur le contenu [Termes IGN] récupération de données [Termes IGN] structure-from-motion [Termes IGN] système d'information géographique Résumé : (auteur) The idea of virtual time machines in digital environments like hand-held virtual reality or four-dimensional (4D) geographic information systems requires an accurate positioning and orientation of urban historical images. The browsing of large repositories to retrieve historical images and their subsequent precise pose estimation is still a manual and time-consuming process in the field of Cultural Heritage. This contribution presents an end-to-end pipeline from finding relevant images with utilization of content-based image retrieval to photogrammetric pose estimation of large historical terrestrial image datasets. Image retrieval as well as pose estimation are challenging tasks and are subjects of current research. Thereby, research has a strong focus on contemporary images but the methods are not considered for a use on historical image material. The first part of the pipeline comprises the precise selection of many relevant historical images based on a few example images (so called query images) by using content-based image retrieval. Therefore, two different retrieval approaches based on convolutional neural networks (CNN) are tested, evaluated, and compared with conventional metadata search in repositories. Results show that image retrieval approaches outperform the metadata search and are a valuable strategy for finding images of interest. The second part of the pipeline uses techniques of photogrammetry to derive the camera position and orientation of the historical images identified by the image retrieval. Multiple feature matching methods are used on four different datasets, the scene is reconstructed in the Structure-from-Motion software COLMAP, and all experiments are evaluated on a newly generated historical benchmark dataset. A large number of oriented images, as well as low error measures for most of the datasets, show that the workflow can be successfully applied. Finally, the combination of a CNN-based image retrieval and the feature matching methods SuperGlue and DISK show very promising results to realize a fully automated workflow. Such an automated workflow of selection and pose estimation of historical terrestrial images enables the creation of large-scale 4D models. Numéro de notice : A2021-827 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110748 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.3390/ijgi10110748 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98964 [article]

Feature matching for multi-epoch historical aerial images / Lulin Zhang in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)    

Public [article]  inISPRS Journal of photogrammetry and remote sensing > Vol 182 (December 2021) . - pp 176 - 189 Titre : Feature matching for multi-epoch historical aerial images Type de document : Article/Communication Auteurs : Lulin Zhang , Auteur ; Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2021 Article en page(s) : pp 176 - 189 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement de données localisées [Termes IGN] chaîne de traitement [Termes IGN] géoréférencement indirect [Termes IGN] image ancienne [Termes IGN] image multitemporelle [Termes IGN] image RVB [Termes IGN] méthode robuste [Termes IGN] MicMac [Termes IGN] modèle numérique de surface [Termes IGN] orientation relative [Termes IGN] point d'appui [Termes IGN] transformation de Helmert Résumé : (auteur) Historical imagery is characterized by high spatial resolution and stereoscopic acquisitions, providing a valuable resource for recovering 3D land-cover information. Accurate geo-referencing of diachronic historical images by means of self-calibration remains a bottleneck because of the difficulty to find sufficient amount of feature correspondences under evolving landscapes. In this research, we present a fully automatic approach to detecting feature correspondences between historical images taken at different times (i.e., inter-epoch), without auxiliary data required. Based on relative orientations computed within the same epoch (i.e., intra-epoch), we obtain DSMs (Digital Surface Model) and incorporate them in a rough-to-precise matching. The method consists of: (1) an inter-epoch DSMs matching to roughly co-register the orientations and DSMs (i.e, the 3D Helmert transformation), followed by (2) a precise inter-epoch feature matching using the original RGB images. The innate ambiguity of the latter is largely alleviated by narrowing down the search space using the co-registered data. With the inter-epoch feature correspondences, we refine the image orientations and quantitatively evaluate the results (1) with DoD (Difference of DSMs), (2) with ground check points, and (3) by quantifying ground displacement due to an earthquake. We demonstrate that our method: (1) can automatically georeference diachronic historical images; (2) can effectively mitigate systematic errors induced by poorly estimated camera parameters; (3) is robust to drastic scene changes. Compared to the state-of-the-art, our method improves the image georeferencing accuracy by a factor of 2. The proposed methods are implemented in MicMac, a free, open-source photogrammetric software. Numéro de notice : A2021-781 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.10.008 Date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.10.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98933 [article]

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Accurate mapping method for UAV photogrammetry without ground control points in the map projection frame / Jianchen Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 9673 - 9681 Titre : Accurate mapping method for UAV photogrammetry without ground control points in the map projection frame Type de document : Article/Communication Auteurs : Jianchen Liu, Auteur ; Wei Xu, Auteur ; Bingxuan Guo, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 9673 - 9681 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] aérotriangulation [Termes IGN] autoétalonnage [Termes IGN] compensation par faisceaux [Termes IGN] courbure de la Terre [Termes IGN] distorsion d'image [Termes IGN] données GNSS [Termes IGN] hauteur de vol [Termes IGN] image captée par drone [Termes IGN] point d'appui [Termes IGN] précision altimétrique [Termes IGN] précision cartographique [Termes IGN] projection Résumé : (auteur) Unmanned aerial vehicle (UAV) photogrammetry without ground control points (GCPs) can effectively improve production efficiency and reduce production costs; this method is especially advantageous in areas that are difficult for people to reach. However, there are a series of problems in UAV photogrammetry without GCPs. One of the main problems is that the accurate camera parameters cannot be obtained through the on-the-job calibration method; furthermore, the inaccurate principal distance will have a serious impact on the elevation accuracy of object points. The other one is that the projection deformation and earth curvature also have impacts on the elevation accuracy, when the mapping task is carried out in the map projection frame. This article explains the specific reasons of elevation errors and proposes an effective solution. First, the camera self-calibration is performed in a geocentric frame with control strips. Then, the exterior orientation elements of the images are calculated in the map projection frame without control strips. Finally, the elevation errors that are caused by the map projection deformation and the earth’s curvature are corrected. The experimental results show that the proposed method can achieve accurate mapping, and the elevation accuracy has been significantly improved. Numéro de notice : A2021-811 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3052466 Date de publication en ligne : 29/01/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3052466 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98884 [article]

Determining optimal photogrammetric adjustment of images obtained from a fixed-wing UAV / Karolina Pargiela in Photogrammetric record, Vol 36 n° 175 (September 2021)  

Public [article]  inPhotogrammetric record > Vol 36 n° 175 (September 2021) . - pp 285 - 302 Titre : Determining optimal photogrammetric adjustment of images obtained from a fixed-wing UAV Type de document : Article/Communication Auteurs : Karolina Pargiela, Auteur ; Antoni Rzonca, Auteur Année de publication : 2021 Article en page(s) : pp 285 - 302 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] acquisition d'images [Termes IGN] chevauchement [Termes IGN] compensation par faisceaux [Termes IGN] image captée par drone [Termes IGN] obturateur [Termes IGN] point d'appui [Termes IGN] Pologne [Termes IGN] positionnement cinématique en temps réel [Termes IGN] structure-from-motion [Termes IGN] système de numérisation mobile Résumé : (auteur) Photogrammetry with unmanned aerial vehicles (UAVs) has become a source of data with extensive applications. The accuracy is of utmost significance, yet the intention is also to find the best possible solutions for data acquisition in economic terms. The objective of the research was the analysis of various variants of the bundle block adjustment. The analysis concerns data which is diversified with respect to the type of shutter (rolling/global), the measurement of external orientation elements, the overlap and the number of ground control points (GCPs). Numéro de notice : A2021-691 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12377 Date de publication en ligne : 07/08/2021 En ligne : https://doi.org/10.1111/phor.12377 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98487 [article]

Three-dimensional building change detection using object-based image analysis (case study: Tehran) / Fatemeh Tabib Mahmoudi in Applied geomatics, vol 13 n° 3 (September 2021)  

Public [article]  inApplied geomatics > vol 13 n° 3 (September 2021) . - pp 325 - 332 Titre : Three-dimensional building change detection using object-based image analysis (case study: Tehran) Type de document : Article/Communication Auteurs : Fatemeh Tabib Mahmoudi, Auteur ; Sharareh Hosseini, Auteur Année de publication : 2021 Article en page(s) : pp 325 - 332 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse d'image orientée objet [Termes IGN] analyse diachronique [Termes IGN] Bâti-3D [Termes IGN] détection de changement [Termes IGN] détection du bâti [Termes IGN] extraction de traits caractéristiques [Termes IGN] gestion urbaine [Termes IGN] hauteur du bâti [Termes IGN] Matlab [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle numérique de surface [Termes IGN] segmentation d'image [Termes IGN] Téhéran Résumé : (auteur) Natural disasters such as earthquakes and floods together with the urban sprawl conducted by increasing the population make multi-temporal changes in building areas. Destruction, buildings’ renovation, and constructing new buildings are the main changes of the urban areas that should be detected to update three-dimensional city models. The results of performing three-dimensional changes detecting of high altitude objects such as buildings are more close to reality than the two-dimensional methods. In this study, a three-dimensional changes detection method is proposed based on digital elevation models (DEMs). In the first step of this proposed method, the normalized digital surface model (nDSM) is generated for timely datasets. Then, object-based image analysis is utilized by performing segmentation followed by the structural classification of DEMs. Differencing and comparing the multi-temporal classification maps as the third step of the proposed algorithm led to analyzing the occurred changes. The obtained results are evaluated in an urban area in Tehran, Iran, in a 9-year time interval. These results represent −9.7% decreasing rate in low-rise buildings and also −1.37% decreases in the ground. Moreover, the class of high-rise buildings increased for +16.4% which conforms to making new constructions in addition to the renovation of low-rise buildings. According to the area analyzing of the changes, 4.8% of the investigated study area has new constructions, 3.05% has buildings’ renovation, and 3.89% has destruction in that 9-year period. Numéro de notice : A2021-623 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00349-w Date de publication en ligne : 07/01/2021 En ligne : https://doi.org/10.1007/s12518-020-00349-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98247 [article]

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)  

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A unified framework of bundle adjustment and feature matching for high-resolution satellite images / Xiao Ling in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)  

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Automated calibration of smartphone cameras for 3D reconstruction of mechanical pipes / Reza Maalek in Photogrammetric record, vol 36 n° 174 (June 2021)  

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Geometric calibration of satellite laser altimeters based on waveform matching / Shaoning Li in Photogrammetric record, vol 36 n° 174 (June 2021)  

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Robust detection of non-overlapping ellipses from points with applications to circular target extraction in images and cylinder detection in point clouds / Reza Maalek in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

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Digital terrain models generated with low-cost UAV photogrammetry: Methodology and accuracy / Sergio Jiménez-Jiménez in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)  

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Implementation of close range photogrammetry using modern non-metric digital cameras for architectural documentation / Mariem A. Elhalawani in Geodesy and cartography, vol 47 n° 1 (January 2021)  

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Automated registration of SfM‐MVS multitemporal datasets using terrestrial and oblique aerial images / Luigi Parente in Photogrammetric record, vol 36 n° 173 (March 2021)  

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AI4GEO: a data intelligence platform for 3D geospatial mapping / Pierre-Marie Brunet (2021)  

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Deep learning for feature based image matching / Lin Chen (2021)  

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