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Improved camera distortion correction and depth estimation for lenslet light field camera / Changkun Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 3 (March 2019) . - pp 197 - 208 Titre : Improved camera distortion correction and depth estimation for lenslet light field camera Type de document : Article/Communication Auteurs : Changkun Yang, Auteur ; Zhaoqin Liu, Auteur ; Kaichang Di, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 197 - 208 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] chambre de prise de vue numérique [Termes descripteurs IGN] correction géométrique [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] modèle géométrique de prise de vue Résumé : (Auteur) A light field camera can capture both radiance and angular information, providing a novel solution for depth estimation. The paper proposes two improved methods including distortion model optimization and depth estimation refinement for a lenslet light field camera. For distortion model optimization, a novel 14-parameter distortion model that involves sub-aperture images generation is applied to correct the light field camera images. For depth estimation refinement, an algorithm reducing the high influence of outliers on depth estimation in weak texture regions is proposed based on multi-view stereo matching using the cost volume. Experimental results show the projection error has decreased by about 30% and the depth root-mean-squared error on real world images has decreased by about 42% with our distortion correction method and depth estimation method compared with state of art algorithms. It verifies the correctness and effectiveness of our proposed methods and show significant improvement on accuracy of depth map estimation. Numéro de notice : A2019-148 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.3.197 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.14358/PERS.85.3.197 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92477 [article]

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Geometric camera pose refinement with learned depth maps / Nathan Piasco (2019)  

Public Titre : Geometric camera pose refinement with learned depth maps Type de document : Article/Communication Auteurs : Nathan Piasco , Auteur ; Désiré Sidibé, Auteur ; Cédric Demonceaux, Auteur ; Valérie Gouet-Brunet , Auteur Congrès : ICIP 2019, 26th IEEE International Conference on Image Processing (22 - 25 septembre 2019; Taipei, Taiwan), Commanditaire Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN Année de publication : 2019 Autre Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Projets : PLaTINUM / Gouet-Brunet, Valérie Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme ICP [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] scène intérieure [Termes descripteurs IGN] semis de points Résumé : (auteur) We present a new method for image-only camera relocalisation composed of a fast image indexing retrieval step followed by pose refinement based on ICP (Iterative Closest Point). The first step aims to find an initial pose for the query by evaluating images similarity with low dimensional global deep descriptors. Subsequently, we predict with a fully convolutional deep encoder-decoder neural network a dense depth map from the image query. We use this depth map to create a local point cloud and refine the initial query pose using an ICP algorithm.We demonstrate the effectiveness of our new approach on various indoor scenes. Compared to learned pose regression methods, our proposal can be used on multiple scenes without the need of a specific weights-setup for each scene, while showing equivalent results. Numéro de notice : C2019-015 Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2019.8803014 date de publication en ligne : 26/08/2019 En ligne : https://doi.org/10.1109/ICIP.2019.8803014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93279

EMVS : Event-based Multi-View Stereo : 3D reconstruction with an event camera in real-time / Henri Rebecq in International journal of computer vision, vol 126 n° 12 (December 2018)  

Public [article]  inInternational journal of computer vision > vol 126 n° 12 (December 2018) . - pp 1394 - 1414 Titre : EMVS : Event-based Multi-View Stereo : 3D reconstruction with an event camera in real-time Type de document : Article/Communication Auteurs : Henri Rebecq, Auteur ; Guillermo Gallego, Auteur ; Elias Mueggler, Auteur ; Davide Scaramuzza, Auteur Année de publication : 2018 Article en page(s) : pp 1394 - 1414 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] caméra d'événement [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] luminance lumineuse [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] temps réel Résumé : (Auteur) Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the output is composed of a sequence of asynchronous events rather than actual intensity images, traditional vision algorithms cannot be applied, so that a paradigm shift is needed. We introduce the problem of event-based multi-view stereo (EMVS) for event cameras and propose a solution to it. Unlike traditional MVS methods, which address the problem of estimating dense 3D structure from a set of known viewpoints, EMVS estimates semi-dense 3D structure from an event camera with known trajectory. Our EMVS solution elegantly exploits two inherent properties of an event camera: (1) its ability to respond to scene edges—which naturally provide semi-dense geometric information without any pre-processing operation—and (2) the fact that it provides continuous measurements as the sensor moves. Despite its simplicity (it can be implemented in a few lines of code), our algorithm is able to produce accurate, semi-dense depth maps, without requiring any explicit data association or intensity estimation. We successfully validate our method on both synthetic and real data. Our method is computationally very efficient and runs in real-time on a CPU. Numéro de notice : A2018-597 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s11263-017-1050-6 date de publication en ligne : 07/11/2017 En ligne : https://doi.org/10.1007/s11263-017-1050-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92524 [article]

3D reconstruction from multi-view VHR-satellite images in MicMac / Ewelina Rupnik in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 201 - 211 Titre : 3D reconstruction from multi-view VHR-satellite images in MicMac Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Arthur Delorme, Auteur Année de publication : 2018 Projets : TOSCA / Le Bris, Arnaud Article en page(s) : pp 201 - 211 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] compensation par bloc [Termes descripteurs IGN] image Pléiades-HR [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] MicMac [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle par fonctions rationnelles [Termes descripteurs IGN] programmation dynamique Résumé : (Auteur) This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities. Numéro de notice : A2018-117 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.016 date de publication en ligne : 20/03/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89553 [article]

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Global, dense multiscale reconstruction for a billion points / Benjamin Ummenhofer in International journal of computer vision, vol 125 n° 1-3 (December 2017)  

Public [article]  inInternational journal of computer vision > vol 125 n° 1-3 (December 2017) . - pp 82 - 94 Titre : Global, dense multiscale reconstruction for a billion points Type de document : Article/Communication Auteurs : Benjamin Ummenhofer, Auteur ; Thomas Brox, Auteur Année de publication : 2017 Article en page(s) : pp 82 - 94 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] carte de profondeur [Termes descripteurs IGN] discrétisation [Termes descripteurs IGN] maillage [Termes descripteurs IGN] méthode des éléments finis [Termes descripteurs IGN] octree [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] reconstruction d'objet Résumé : (Auteur) We present a variational approach for surface reconstruction from a set of oriented points with scale information. We focus particularly on scenarios with nonuniform point densities due to images taken from different distances. In contrast to previous methods, we integrate the scale information in the objective and globally optimize the signed distance function of the surface on a balanced octree grid. We use a finite element discretization on the dual structure of the octree minimizing the number of variables. The tetrahedral mesh is generated efficiently with a lookup table which allows to map octree cells to the nodes of the finite elements. We optimize memory efficiency by data aggregation, such that robust data terms can be used even on very large scenes. The surface normals are explicitly optimized and used for surface extraction to improve the reconstruction at edges and corners. Numéro de notice : A2017-814 Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s11263-017-1017-7 En ligne : https://doi.org/10.1007/s11263-017-1017-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89256 [article]

Efficient edge-aware surface mesh reconstruction for urban scenes / András Bódis-Szomorú in Computer Vision and image understanding, vol 157 (April 2017)  

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Generalizing the prediction sum of squares statistic and formula, application to linear fractional image warp and surface fitting / Adrien Bartoli in International journal of computer vision, vol 122 n° 1 (March 2017)  

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Joint inpainting of depth and reflectance with visibility estimation / Marco Bevilacqua in ISPRS Journal of photogrammetry and remote sensing, vol 125 (March 2017)  

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Development of a SGM-based multi-view reconstruction framework for aerial imagery / Mathias Rothermel (2016) 

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Visibility estimation and joint inpainting of lidar depth maps / Marco Bevilacqua (2016)  

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Géodésie multi-technique pour la surveillance haute fréquence de glissements de terrains / Pierre Boetzle (2015) 

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Simulating spatial aspects of a flash flood using the Monte Carlo method and GRASS GIS: a case study of the Malá Svinka Basin (Slovakia) / Jaroslav Hofierka in Open geosciences, vol 7 n° 1 (January 2015)  

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3D range scan enhancement using image-based methods / Steffen Herbort in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)

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Appariement entre images de point de vue éloignés par utilisation de carte de profondeur / Narut Soontranon (2013) 

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Automated detection of prehistorical rock art features aided by TLS and 2D data co-registration / Jean-Baptiste Lamontre (2012)

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