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A robust nonrigid point set registration framework based on global and intrinsic topological constraints / Guiqiang Yang in The Visual Computer, vol 38 n° 2 (February 2022)  

Public [article]  inThe Visual Computer > vol 38 n° 2 (February 2022) . - pp 603 - 623 Titre : A robust nonrigid point set registration framework based on global and intrinsic topological constraints Type de document : Article/Communication Auteurs : Guiqiang Yang, Auteur ; Rui Li, Auteur ; Yujun Liu, Auteur ; Ji Wang, Auteur Année de publication : 2022 Article en page(s) : pp 603 - 623 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] algorithme espérance-maximisation [Termes IGN] contrainte géométrique [Termes IGN] contrainte topologique [Termes IGN] descripteur local [Termes IGN] méthode fondée sur le noyau [Termes IGN] méthode robuste [Termes IGN] processus gaussien [Termes IGN] semis de points [Termes IGN] superposition de données Résumé : (auteur) The problem of registering nonrigid point sets, with the aim of estimating the correspondences and learning the transformation between two given sets of points, often arises in computer vision tasks. This paper proposes a novel method for performing nonrigid point set registration on data with various types of degradation, in which the registration problem is formulated as a Gaussian mixture model (GMM)-based density estimation problem. Specifically, two complementary constraints are jointly considered for optimization in a GMM probabilistic framework. The first is a thin-plate spline-based regularization constraint that maintains global spatial motion consistency, and the second is a spectral graph-based regularization constraint that preserves the intrinsic structure of a point set. Moreover, the correspondences and the transformation are alternately optimized using the expectation maximization algorithm to obtain a closed-form solution. We first utilize local descriptors to construct the initial correspondences and then estimate the underlying transformation under the GMM-based framework. Experimental results on contour images and real images show the effectiveness and robustness of the proposed method. Numéro de notice : A2022-146 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s00371-020-02037-7 Date de publication en ligne : 21/02/2022 En ligne : https://doi.org/10.1007/s00371-020-02037-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100040 [article]

Semi-automatic extraction of rural roads under the constraint of combined geometric and texture features / Hai Tan 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) . - pp 754 Titre : Semi-automatic extraction of rural roads under the constraint of combined geometric and texture features Type de document : Article/Communication Auteurs : Hai Tan, Auteur ; Zimo Shen, Auteur ; Jiguang Dai, Auteur Année de publication : 2021 Article en page(s) : pp 754 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] chemin rural [Termes IGN] Chine [Termes IGN] coefficient de corrélation [Termes IGN] contrainte géométrique [Termes IGN] corrélation croisée normalisée [Termes IGN] courbure [Termes IGN] extraction de traits caractéristiques [Termes IGN] extraction semi-automatique [Termes IGN] image à haute résolution [Termes IGN] modèle de simulation [Termes IGN] niveau de gris (image) [Termes IGN] route [Termes IGN] texture Résumé : (auteur) The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can easily lead to problems involving the similarity of the road texture with the texture of surrounding objects and make it difficult to improve the automation of traditional high-precision road extraction methods. Based on this background, a semi-automatic rural road extraction method constrained by a combination of geometric and texture features is proposed in this paper. First, an adaptive road width extraction model is proposed to improve the accuracy of the initial road centre point. Then, aiming at the continuous change of curvature of rural roads, a tracking direction prediction model is proposed. Finally, a matching model under geometric texture constraints is proposed, which solves the problem of similarity between road and neighbourhood texture to a certain extent. The experimental results show that by selecting different types of experimental scenes or remotely sensed image data, compared with other methods, the proposed method can not only guarantee the road extraction accuracy but also improve the degree of automation to a certain extent. Numéro de notice : A2021-850 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110754 Date de publication en ligne : 09/11/2021 En ligne : https://doi.org/10.3390/ijgi10110754 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99009 [article]

Using geometric constraints to improve performance of image classifiers for automatic segmentation of traffic signs / Roholah Yazdan in Geomatica [en ligne], vol 75 n° 1 (Mars 2021)  

Public [article]  inGeomatica [en ligne] > vol 75 n° 1 (Mars 2021) . - pp 28 - 50 Titre : Using geometric constraints to improve performance of image classifiers for automatic segmentation of traffic signs Type de document : Article/Communication Auteurs : Roholah Yazdan, Auteur ; Masood Varshosaz, Auteur ; Saied Pirasteh, Auteur ; Fabio Remondino, Auteur Année de publication : 2021 Article en page(s) : pp 28 - 50 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] contrainte géométrique [Termes IGN] espace colorimétrique [Termes IGN] programmation par contraintes [Termes IGN] signalisation routière Résumé : (auteur) Automatic detection and recognition of traffic signs from images is an important topic in many applications. At first, we segmented the images using a classification algorithm to delineate the areas where the signs are more likely to be found. In this regard, shadows, objects having similar colours, and extreme illumination changes can significantly affect the segmentation results. We propose a new shape-based algorithm to improve the accuracy of the segmentation. The algorithm works by incorporating the sign geometry to filter out the wrong pixels from the classification results. We performed several tests to compare the performance of our algorithm against those obtained by popular techniques such as Support Vector Machine (SVM), K-Means, and K-Nearest Neighbours. In these tests, to overcome the unwanted illumination effects, the images are transformed into colour spaces Hue, Saturation, and Intensity, YUV, normalized red green blue, and Gaussian. Among the traditional techniques used in this study, the best results were obtained with SVM applied to the images transformed into the Gaussian colour space. The comparison results also suggested that by adding the geometric constraints proposed in this study, the quality of sign image segmentation is improved by 10%–25%. We also comparted the SVM classifier enhanced by incorporating the geometry of signs with a U-Shaped deep learning algorithm. Results suggested the performance of both techniques is very close. Perhaps the deep learning results could be improved if a more comprehensive data set is provided. Numéro de notice : A2021-608 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1139/geomat-2020-0010 En ligne : https://doi.org/10.1139/geomat-2020-0010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98322 [article]

Exploiting multi-camera constraints within bundle block adjustment: an experimental comparison / Eleonora Maset (2021)  

Public Titre : Exploiting multi-camera constraints within bundle block adjustment: an experimental comparison Type de document : Article/Communication Auteurs : Eleonora Maset, Auteur ; Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Fabio Remondino, Auteur ; Andrea Fusiello, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2021 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B2-2021 Projets : 1-Pas de projet / Conférence : ISPRS 2021, Commission 2, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Archives Commission 2 Importance : pp 33 - 38 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] aérotriangulation numérique [Termes IGN] analyse comparative [Termes IGN] compensation par faisceaux [Termes IGN] contrainte géométrique [Termes IGN] image oblique [Termes IGN] image terrestre [Termes IGN] instrumentation Leica [Termes IGN] orientation relative [Termes IGN] Stéréopolis Résumé : (auteur) The growing deployment of multi-head camera systems encouraged the emergence of specific processing algorithms, able to face the challenges posed by slanted view geometry. Such multi-camera systems are rigidly tied by their manufacturers hence the exploitation of this internal constraint should be further exploited. Several approaches have been proposed to deal with orientation constraints, with the aim of reducing the number of unknowns, computational time and possibly improve the accuracy. In this paper we compare the results provided by publicly available implementations in order to further investigate the advantages of enforcing relative orientation constraints for aerial and terrestrial triangulation of multi-head camera systems. Data from a Leica CityMapper and a Stereopolis-Ladybug are considered, reporting how constrained solution can improve accuracy with respect to traditional (unconstrained) bundle block adjustment solutions. Numéro de notice : C2021-013 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B2-2021-33-2021 Date de publication en ligne : 28/06/2021 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-33-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98063

Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds / Yuan Li in Remote sensing, vol 13 n° 1 (January-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January-1 2021) . - n° 13 Titre : Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds Type de document : Article/Communication Auteurs : Yuan Li, Auteur ; Wu Bo, Auteur Année de publication : 2021 Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] CityGML [Termes IGN] contrainte géométrique [Termes IGN] détection de contours [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] géomètrie algorithmique [Termes IGN] Ransac (algorithme) [Termes IGN] reconstruction 3D du bâti [Termes IGN] relation topologique [Termes IGN] semis de points [Termes IGN] ville intelligente Résumé : (auteur) The complexity and variety of buildings and the defects of point cloud data are the main challenges faced by 3D urban reconstruction from point clouds, especially in metropolitan areas. In this paper, we developed a method that embeds multiple relations into a procedural modelling process for the automatic 3D reconstruction of buildings from photogrammetric point clouds. First, a hybrid tree of constructive solid geometry and boundary representation (CSG-BRep) was built to decompose the building bounding space into multiple polyhedral cells based on geometric-relation constraints. The cells that approximate the shapes of buildings were then selected based on topological-relation constraints and geometric building models were generated using a reconstructing CSG-BRep tree. Finally, different parts of buildings were retrieved from the CSG-BRep trees, and specific surface types were recognized to convert the building models into the City Geography Markup Language (CityGML) format. The point clouds of 105 buildings in a metropolitan area in Hong Kong were used to evaluate the performance of the proposed method. Compared with two existing methods, the proposed method performed the best in terms of robustness, regularity, and topological correctness. The CityGML building models enriched with semantic information were also compared with the manually digitized ground truth, and the high level of consistency between the results suggested that the produced models will be useful in smart city applications. Numéro de notice : A2021-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010129 Date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.3390/rs13010129 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96820 [article]

Improving GNSS-acoustic positioning by optimizing the ship’s track lines and observation combinations / Guanxu Chen in Journal of geodesy, vol 94 n° 6 (June 2020)  

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An indoor spatial accessible area generation approach considering distance constraints / Lina Yang in Annals of GIS, Vol 26 n° 1 (January 2020)  

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Learning stereo reconstruction with deep neural networks / Stepan Tulyakov (2020)  

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Reliable image matching via photometric and geometric constraints structured by Delaunay triangulation / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 153 (July 2019)  

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Geometric reasoning with uncertain polygonal faces / Jochen Meidow in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 6 (juin 2018)  

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SDF-2-SDF registration for real-time 3D reconstruction from RGB-D data / Miroslava Slavcheva in International journal of computer vision, vol 126 n° 6 (June 2018)  

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Recognizing building groups for generalization : a comparative study / Min Deng in Cartography and Geographic Information Science, Vol 45 n° 3 (May 2018)  

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An immune genetic algorithm to buildings displacement in cartographic generalization / Yageng Sun in Transactions in GIS, vol 20 n° 4 (August 2016)  

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Camera self-calibration with lens distortion from a single image / Dan Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)  

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Midrange geometric interactions for semantic segmentation / Julia Diebold in International journal of computer vision, vol 117 n° 3 (May 2016)  

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