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Feature matching for multi-epoch historical aerial images: A new pipeline feature detection pipeline in open-source MicMac / Lulin Zhang in Blog de la RFPT, sans n° ([17/11/2021])  

Public [article]  inBlog de la RFPT > sans n° [17/11/2021] Titre : Feature matching for multi-epoch historical aerial images: A new pipeline feature detection pipeline in open-source MicMac Type de document : Article/Communication Auteurs : Lulin Zhang , Auteur ; Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2021 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement de formes [Termes IGN] chaîne de traitement [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] détection de changement [Termes IGN] données multitemporelles [Termes IGN] image aérienne [Termes IGN] image ancienne [Termes IGN] image RVB [Termes IGN] MicMac [Termes IGN] modèle numérique de surface Résumé : (Auteur) [Introduction] ... We propose a fully automatic approach to computing robust inter-epoch feature correspondences. Our method consists of two steps: a rough co-registration by finding feature correspondences between DSMs (Digital Surface Model) derived within single epochs, and a precise feature matching on original RGB images. Our main contributions include: - Rough-to-precise matching strategy that helps to drastically reduce ambiguity. In particular, we use the depth information to roughly co-register our epochs. The 3D landscape is globally stable over time and provides sufficient correspondences through time. Once co-registered, we levarage the 3D a priori to narrow down the search space in precise matching. - Upscaling of the learning based feature matching algorithms to high resolution imagery. To do that, we introduced an image tiling scheme. In the following we present the methodology and some experiments. If you are interested in using our method, please refer to the source code of MicMac Github 4, as well as 2 jupyter tutorials 5 6. We also provide an introduction video 7, slides 8 and project website 9. The datasets used in our publication 3 will be soon published in an open-access repository. Numéro de notice : A2021-840 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 17/11/2021 En ligne : https://rfpt-sfpt.github.io/blog/feature%20matching/historical%20images/multi-ep [...] Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99042 [article]

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]

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)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 7 (July 2021) . - pp 485 - 490 Titre : A unified framework of bundle adjustment and feature matching for high-resolution satellite images Type de document : Article/Communication Auteurs : Xiao Ling, Auteur ; Xu Huang, Auteur ; Rongjun Qin, Auteur Année de publication : 2021 Article en page(s) : pp 485 - 490 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement d'images [Termes IGN] compensation par faisceaux [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] image à haute résolution [Termes IGN] orientation du capteur [Termes IGN] précision radiométrique Résumé : (Auteur) Bundle adjustment (BA) is a technique for refining sensor orientations of satellite images, while adjustment accuracy is correlated with feature matching results. Feature matching often contains high uncertainties in weak/repeat textures, while BA results are helpful in reducing these uncertainties. To compute more accurate orientations, this article incorporates BA and feature matching in a unified framework and formulates the union as the optimization of a global energy function so that the solutions of the BA and feature matching are constrained with each other. To avoid a degeneracy in the optimization, we propose a comprised solution by breaking the optimization of the global energy function into two-step suboptimizations and compute the local minimums of each suboptimization in an incremental manner. Experiments on multi-view high-resolution satellite images show that our proposed method outperforms state-of-the-art orientation techniques with or without accurate least-squares matching. Numéro de notice : A2021-571 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.7.485 Date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.14358/PERS.87.7.485 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98163 [article]

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Research on feature extraction method of indoor visual positioning image based on area division of foreground and background / Ping Zheng in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 402 Titre : Research on feature extraction method of indoor visual positioning image based on area division of foreground and background Type de document : Article/Communication Auteurs : Ping Zheng, Auteur ; Danyang Qin, Auteur ; Bing Han, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 402 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] extraction de traits caractéristiques [Termes IGN] logiciel libre [Termes IGN] positionnement en intérieur [Termes IGN] Ransac (algorithme) [Termes IGN] SIFT (algorithme) [Termes IGN] SURF (algorithme) Résumé : (auteur) In the process of indoor visual positioning and navigation, difficult points often exist in corridors, stairwells, and other scenes that contain large areas of white walls, strong consistent background, and sparse feature points. Aiming at the problem of positioning and navigation in the real physical world where the walls with sparse feature points are difficult to be filled with pictures, this paper designs a feature extraction method, ARAC (Adaptive Region Adjustment based on Consistency) using Free and Open-Source Software and tools. It divides the image into foreground and background and extracts their features respectively, to achieve not only retain positioning information but also focus more energy on the foreground area which is favourable for navigation. In the test phase, under the combined conditions of illumination, scale and affine changes, the feature matching maps by the feature extraction algorithm proposed in this paper are compared with those by SIFT and SURF. Experiments show that the number of correctly matched feature pairs obtained by ARAC is better than SIFT and SURF, and whose time of feature extraction and matching is comparable to SURF, which verifies the accuracy and efficiency of the ARAC feature extraction method. Numéro de notice : A2021-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi10060402 Date de publication en ligne : 11/06/2021 En ligne : https://doi.org/10.3390/ijgi10060402 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97940 [article]

Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation / Roholah Yazdan in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 18 - 35 Titre : Improving traffic sign recognition results in urban areas by overcoming the impact of scale and rotation Type de document : Article/Communication Auteurs : Roholah Yazdan, Auteur ; Masood Varshosaz, Auteur Année de publication : 2021 Article en page(s) : pp 18 - 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] base de données d'images [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] corrélation à l'aide de traits caractéristiques [Termes IGN] corrélation croisée normalisée [Termes IGN] couple stéréoscopique [Termes IGN] détection automatique [Termes IGN] modèle stéréoscopique [Termes IGN] reconnaissance d'objets [Termes IGN] segmentation d'image [Termes IGN] SIFT (algorithme) [Termes IGN] signalisation routière [Termes IGN] SURF (algorithme) [Termes IGN] Téhéran [Termes IGN] transformation de Hough [Termes IGN] zone urbaine Résumé : (auteur) Automatic detection and recognition of traffic signs have many applications. However, some problems can affect the accuracy of the existing algorithms, such as changes in environmental light conditions, shadows, the presence of objects of the same colour, significant changes in scale and rotation, as well as obstacles in front of the traffic signs. To overcome these difficulties, a reference image database is usually used that includes different modes of appearing the traffic signs in the images. In order to overcome the effects of scale and rotation, in this paper a new method is presented in which only one reference image is needed for each sign to recognise the traffic sign in an image. In the proposed method, imaging is done in stereo. Using the captured image pair, a virtual image is generated which is then used to recognise the sign. As a result, the recognition is carried out with a minimum number of reference images. Experiments show that the proposed algorithm significantly improves recognition results. The traffic signs are recognised with 93.1% accuracy that enjoys a 4.9% improvement over traditional methods. Numéro de notice : A2021-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.003 Date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.003 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96304 [article]

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A LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching / Chuang Qian in Journal of geodesy, vol 94 n° 10 (October 2020)  

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BIM-Tracker: A model-based visual tracking approach for indoor localisation using a 3D building model / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

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An effective ensemble classification framework using random forests and a correlation based feature selection technique / Dibyajyoti Chutia in Transactions in GIS, vol 21 n° 6 (December 2017)  

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Accurate affine invariant image matching using oriented least square / Amin Sedaghat in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 9 (September 2015)

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Graph-based synchronous collaborative mapping / Xiaochen Kang in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)  

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Une méthode de construction de données spatio-temporelles pour l'étude de l'espace urbain ancien / Bertrand Duménieu (2013)    

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Spectral Feature Selection for Data Mining / Zheng Alan Zhao (2011)  

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Analyse et développement d’outils permettant de quantifier les problèmes de continuité au niveau des raccords dans une mosaïque d’ortho-images / M. Jaussaud (2010) 

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A formulation for unsupervised hierarchical segmentation of facade images with periodic models / Jean-Pascal Burochin (2010)  

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3D road mark reconstruction from multiple calibrated aerial images / Olivier Tournaire (2006)    

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