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Automatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios / Klemen Istenič in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 13 - 25 Titre : Automatic scale estimation of structure from motion based 3D models using laser scalers in underwater scenarios Type de document : Article/Communication Auteurs : Klemen Istenič, Auteur ; Nuno Gracias, Auteur ; Aurélien Arnaubec, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 13 - 25 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] étalonnage [Termes descripteurs IGN] faisceau laser [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image sous-marine [Termes descripteurs IGN] photogrammétrie sous-marine [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) Improvements in structure-from-motion techniques are enabling many scientific fields to benefit from the routine creation of detailed 3D models. However, for a large number of applications, only a single camera is available for the image acquisition, due to cost or space constraints in the survey platforms. Monocular structure-from-motion raises the issue of properly estimating the scale of the 3D models, in order to later use those models for metrology. The scale can be determined from the presence of visible objects of known dimensions, or from information on the magnitude of the camera motion provided by other sensors, such as GPS. This paper addresses the problem of accurately scaling 3D models created from monocular cameras in GPS-denied environments, such as in underwater applications. Motivated by the common availability of underwater laser scalers, we present two novel approaches which are suitable for different laser scaler configurations. A fully unconstrained method enables the use of arbitrary laser setups, while a partially constrained method reduces the need for calibration by only assuming parallelism on the laser beams and equidistance with the camera. The proposed methods have several advantages with respect to existing methods. By using the known geometry of the scene represented by the 3D model, along with some parameters of the laser scaler geometry, the need for laser alignment with the optical axis of the camera is eliminated. Furthermore, the extremely error-prone manual identification of image points on the 3D model, currently required in image-scaling methods, is dispensed with. The performance of the methods and their applicability was evaluated both on data generated from a realistic 3D model and on data collected during an oceanographic cruise in 2017. Three separate laser configurations have been tested, encompassing nearly all possible laser setups, to evaluate the effects of terrain roughness, noise, camera perspective angle and camera-scene distance on the final estimates of scale. In the real scenario, the computation of 6 independent model scale estimates using our fully unconstrained approach, produced values with a standard deviation of 0,3 %. By comparing the values to the only other possible method currently usable for this dataset, we showed that the consistency of scales obtained for individual lasers is much higher for our approach (0,6 % compared to 4 %). Numéro de notice : A2020-010 Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.10.007 date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.10.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94397 [article]

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Robust pose estimation and calibration of catadioptric cameras with spherical mirrors / Sagi Filin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 1 (January 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 1 (January 2020) . - pp 33 - 44 Titre : Robust pose estimation and calibration of catadioptric cameras with spherical mirrors Type de document : Article/Communication Auteurs : Sagi Filin, Auteur ; Grigory Ilizirov, Auteur ; Bashar Elnashef, Auteur Année de publication : 2020 Article en page(s) : pp 33 - 44 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] flux lumineux [Termes descripteurs IGN] lentille [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] miroir [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] sphère [Termes descripteurs IGN] trilatération Résumé : (Auteur) Catadioptric cameras broaden the field of view and reveal otherwise occluded object parts. They differ geometrically from central-perspective cameras because of light reflection from the mirror surface. To handle these effects, we present new pose-estimation and reconstruction models for imaging through spherical mirrors. We derive a closed-form equivalent to the collinearity principle via which three methods are established to estimate the system parameters: a resection-based one, a trilateration-based one that introduces novel constraints that enhance accuracy, and a direct and linear transform-based one. The estimated system parameters exhibit improved accuracy compared to the state of the art, and analysis shows intrinsic robustness to the presence of a high fraction of outliers. We then show that 3D point reconstruction can be performed at accurate levels. Thus, we provide an in-depth look into the geometrical modeling of spherical catadioptric systems and practical enhancements of accuracies and requirements to reach them. Numéro de notice : A2020-050 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.1.33 date de publication en ligne : 01/01/2020 En ligne : https://doi.org/10.14358/PERS.86.1.33 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94535 [article]

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Towards structureless bundle adjustment with two- and three-view structure approximation / Ewelina Rupnik (2020)    

Public contenu dans HAL Hyper articles en ligne / Centre pour la Communication Scientifique Directe CCSD (2000)   Titre : Towards structureless bundle adjustment with two- and three-view structure approximation Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Editeur : Paris : HAL Année de publication : 2020 Importance : 8 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] approximation [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] orientation d'image [Termes descripteurs IGN] précision [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] séquence d'images [Termes descripteurs IGN] structure-from-motion Résumé : (auteur) The global approaches solve SfM problems by independently inferring relative motions, followed be a sequential estimation of global rotations and translations. It is a fast approach but not optimal because it relies only on pairs and triplets of images and it is not a joint optimisation. In this publication we present a methodology that increases the quality of global solutions without the usual computational burden tied to the bundle adjustment. We propose an efficient structure approximation approach that relies on relative motions known upfront. Using the approximated structure, we are capable of refining the initial poses at very low computational cost. Compared to different benchmark datasets and software solutions, our approach improves the processing times while maintaining good accuracy. Numéro de notice : P2020-002 Thématique : IMAGERIE Nature : Preprint nature-HAL : Préprint En ligne : https://hal.archives-ouvertes.fr/hal-02499312 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94722

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Simulation and analysis of photogrammetric UAV image blocks: influence of camera calibration error / Yilin Zhou in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-2/W5 (may 2019)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-2/W5 (may 2019) . - pp 195 - 200 Titre : Simulation and analysis of photogrammetric UAV image blocks: influence of camera calibration error Type de document : Article/Communication Auteurs : Yilin Zhou, Auteur ; Ewelina Rupnik , Auteur ; Christophe Meynard, Auteur ; Christian Thom , Auteur ; Marc Pierrot-Deseilligny , Auteur Congrès : ISPRS Geospatial Week 2019 (10 - 14 juin 2019; Enschede, Pays-Bas), Commanditaire Année de publication : 2019 Article en page(s) : pp 195 - 200 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] bloc d'images [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] effet thermique [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] étalonnage en vol [Termes descripteurs IGN] image aérienne oblique [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] longueur focale [Termes descripteurs IGN] photogrammétrie aérienne [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] point de liaison (imagerie) Résumé : (auteur) Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. The camera calibration for UAV image blocks can be performed a priori or during the bundle block adjustment (self-calibration). For an area of interest with flat, corridor configuration, the focal length of camera is highly correlated with the height of camera. Furthermore, systematic errors of camera calibration accumulate on the longer dimension and cause deformation. Therefore, special precautions must be taken when estimating camera calibration parameters. In this paper, a simulated, error-free aerial image block is generated. error is then added on camera calibration and given as initial solution to bundle block adjustment. Depending on the nature of the error and the investigation purpose, camera calibration parameters are either fixed or re-estimated during the bundle block adjustment. The objective is to investigate how certain errors in the camera calibration impact the accuracy of 3D measurement without the influence of other errors. All experiments are carried out with Fraser camera calibration model being employed. When adopting a proper flight configuration, an error on focal length for the initial camera calibration can be corrected almost entirely during bundle block adjustment. For the case where an erroneous focal length is given for pre-calibration and not re-estimated, the presence of oblique images limits the drift on camera height hence gives better camera pose estimation. Other than that, the error on focal length when neglecting its variation during the acquisition (e.g., due to camera temperature increase) is also investigated; a bowl effect is observed when one focal length is given in camera pre-calibration to the whole image block. At last, a local error is added in image space to simulate camera flaws; this type of error is more difficult to be corrected with the Fraser camera model and the accuracy of 3D measurement degrades substantially. Numéro de notice : A2019-591 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-2-W5-195-2019 date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.5194/isprs-annals-IV-2-W5-195-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94551 [article]

BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images / Debaditya Acharya in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 245 - 258 Titre : BIM-PoseNet: Indoor camera localisation using a 3D indoor model and deep learning from synthetic images Type de document : Article/Communication Auteurs : Debaditya Acharya, Auteur ; Kourosh Khoshelham, Auteur ; Stephan Winter, Auteur Année de publication : 2019 Article en page(s) : pp 245 - 258 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] compréhension de l'image [Termes descripteurs IGN] estimation de pose [Termes descripteurs IGN] image de synthèse [Termes descripteurs IGN] modélisation 3D du bâti BIM [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) The ubiquity of cameras built in mobile devices has resulted in a renewed interest in image-based localisation in indoor environments where the global navigation satellite system (GNSS) signals are not available. Existing approaches for indoor localisation using images either require an initial location or need first to perform a 3D reconstruction of the whole environment using structure-from-motion (SfM) methods, which is challenging and time-consuming for large indoor spaces. In this paper, a visual localisation approach is proposed to eliminate the requirement of image-based reconstruction of the indoor environment by using a 3D indoor model. A deep convolutional neural network (DCNN) is fine-tuned using synthetic images obtained from the 3D indoor model to regress the camera pose. Results of the experiments indicate that the proposed approach can be used for indoor localisation in real-time with an accuracy of approximately 2 m. Numéro de notice : A2019-142 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.020 date de publication en ligne : 05/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92480 [article]

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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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Equivalent constraints for two-view geometry : Pose solution/pure rotation identification and 3D reconstruction / Qi Cai in International journal of computer vision, vol 127 n° 2 (February 2019)  

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

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Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation / Xin Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)  

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Depth-based hand pose estimation : Methods, data, and challenges / James Steven Supančič in International journal of computer vision, vol 126 n° 11 (November 2018)  

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3D urban geovisualization: in situ augmented and mixed reality experiments / Alexandre Devaux in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-4 ([19/09/2018])    

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Image-based synthesis for deep 3D human pose estimation / Grégory Rogez in International journal of computer vision, vol 126 n° 9 (September 2018)  

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Landmark based localization in urban environment / Xiaozhi Qu in ISPRS Journal of photogrammetry and remote sensing, vol 140 (June 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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Real-time accurate 3D head tracking and pose estimation with consumer RGB-D cameras / David Joseph Tan in International journal of computer vision, vol 126 n° 2-4 (April 2018)  

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