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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)
[article]
Titre : Structure from motion for ordered and unordered image sets based on random k-d forests and global pose estimation Type de document : Article/Communication Auteurs : Xin Wang, Auteur ; Franz Rottensteiner, Auteur ; Christian Heipke, Auteur Année de publication : 2019 Article en page(s) : pp 19 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] appariement d'images
[Termes IGN] chaîne de traitement
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] compensation par faisceaux
[Termes IGN] estimation de pose
[Termes IGN] image captée par drone
[Termes IGN] matrice de rotation
[Termes IGN] orientation relative
[Termes IGN] Ransac (algorithme)
[Termes IGN] recouvrement d'images
[Termes IGN] SIFT (algorithme)
[Termes IGN] structure-from-motion
[Termes IGN] vision par ordinateurRésumé : (auteur) In this paper, we present a new fast and robust method for structure from motion (SfM) for data sets potentially comprising thousands of ordered or unordered images. Our work focuses on the two most time-consuming procedures: (a) image matching and (b) pose estimation. For image matching, a new method employing a random k-d forest is proposed to quickly obtain pairs of overlapping images from an unordered set. After that, image matching and the estimation of relative orientation parameters are performed only for pairs found to be very likely to overlap. For pose estimation, we use a two-stage global approach, separating the determination of rotation matrices and translation parameters; the latter are computed simultaneously using a new method. In order to cope with outliers in the relative orientations, which global approaches are particularly sensitive to, we present a new constraint based on triplet loop closure errors of rotation and translation. Finally, a robust bundle adjustment is carried out to refine the image orientation parameters. We demonstrate the potential and limitations of our pipeline using various real-world datasets including ordered image data acquired from UAV (unmanned aerial vehicle) and other platforms as well as unordered data from the internet. The experiments show that our work performs better than comparable state-of-the-art SfM systems in terms of run time, while we achieve a similar accuracy and robustness. Numéro de notice : A2019-033 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.009 Date de publication en ligne : 15/11/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91970
in ISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 19 - 41[article]Réservation
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Titre : Visual object tracking with deep neural networks Type de document : Monographie Auteurs : Pier Luigi Mazzeo, Éditeur scientifique ; Srinivasan Ramakrishnan, Éditeur scientifique ; Paolo Spagnolo, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2019 Importance : 206 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-78985-142-7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] détection d'objet
[Termes IGN] image captée par drone
[Termes IGN] poursuite de cible
[Termes IGN] réseau neuronal artificiel
[Termes IGN] réseau neuronal siamois
[Termes IGN] segmentation sémantique
[Termes IGN] SIFT (algorithme)Résumé : (éditeur) Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research. Note de contenu : 1- Deep siamese networks toward robust visual tracking
2- Multi-person tracking based on faster R-CNN and deep appearance features
3- Detecting and counting small animal species using drone imagery by applying deep learning
4- Deep-facial feature-based person reidentification for authentication in surveillance applications
5- Object re-identification based on deep learning
6- Spatial domain representation for face recognition
7- Extended binary gradient pattern (eBGP): A micro-and macrostructure-based binary gradient pattern for face recognition in video surveillance area
8- Matrix factorization on complex domain for face recognition
9- Granular approach for recognizing surgically altered face Images using keypoint descriptors and artificial neural networkNuméro de notice : 28579 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.80142 En ligne : https://doi.org/10.5772/intechopen.80142 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97854 Automatic building rooftop extraction from aerial images via hierarchical RGB-D priors / Shibiao Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Automatic building rooftop extraction from aerial images via hierarchical RGB-D priors Type de document : Article/Communication Auteurs : Shibiao Xu, Auteur ; Xingjia Pan, Auteur ; Er Li, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 7369 - 7387 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] détection du bâti
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] itération
[Termes IGN] scène urbaine
[Termes IGN] segmentation d'image
[Termes IGN] segmentation hiérarchique
[Termes IGN] toit
[Termes IGN] zone saillante 3DRésumé : (auteur) Accurate building rooftop extraction from high-resolution aerial images is of crucial importance in a wide range of applications. Owing to the varying appearance and large-scale range of scene objects, especially for building rooftops in different scales and heights, single-scale or individual prior-based extraction technique is insufficient in pursuing efficient, generic, and accurate extraction results. The trend toward integrating multiscale or several cue techniques appears to be the best way; thus, such integration is the focus of this paper. We first propose a novel salient rooftop detector integrating four correlative RGB-D priors (depth cue, uniqueness prior, shape prior, and transition surface prior) for improved rooftop extraction to address the preceding complex issues mentioned. Then, these correlative cues are computed from image layers created by our multilevel segmentation and further fused into the state-of-the-art high-order conditional random field (CRF) framework to locate the rooftop. Finally, an iterative optimization strategy is applied for high-quality solving, which can robustly handle varying appearance of building rooftops. Performance evaluations in the SZTAKI-INRIA benchmark data sets show that our method outperforms the traditional color-based algorithm and the original high-order CRF algorithm and its variants. The proposed algorithm is also evaluated and found to produce consistently satisfactory results for various large-scale, real-world data sets. Numéro de notice : A2018-558 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2850972 Date de publication en ligne : 26/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2850972 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91664
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7369 - 7387[article]Geomatics and augmented reality experiments for the cultural heritage / Vicenzo Barrile in Applied geomatics, vol 10 n° 4 (December 2018)
[article]
Titre : Geomatics and augmented reality experiments for the cultural heritage Type de document : Article/Communication Auteurs : Vicenzo Barrile, Auteur ; Antonino Fotia, Auteur ; Giuliana Bilotta, Auteur Année de publication : 2018 Article en page(s) : pp 569 - 578 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Calabre
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] église
[Termes IGN] image captée par drone
[Termes IGN] modèle 3D du site
[Termes IGN] patrimoine archéologique
[Termes IGN] patrimoine culturel
[Termes IGN] patrimoine immobilier
[Termes IGN] réalité augmentée
[Termes IGN] semis de pointsRésumé : (Auteur) For years, the Laboratory of Geomatics of the Mediterranean University of Reggio Calabria has undertaken an interdisciplinary project for the recovery and dissemination of information regarding the cultural-artistic and archeological heritage of the metropolitan area. The combined use of geomatics technologies (laser scanners, GPS positioning, digital photogrammetry, remote sensing, GPR) allows on the one hand to investigate objects and artifacts, providing metric, form, and location information; and on the other, to catalog information and make it accessible to the community. Indeed, the digitalization and reconstruction tools of 3D models can be the answer to the limits related to communicability in the archeological sector. Precision, detail, and very accurate photo-realistic reconstructions are particularly useful for virtual and augmented reality applications, integrating them in the devices used on a daily basis. The present note concerns, therefore, the acquisition of information using the point cloud from UAVs and laser scanners, the subsequent 3D modeling, and their representation in an augmented reality (AR) environment using mobile platforms. The application was tested on the church of Sant’Antonio Abate, located in the North of Reggio Calabria, which according to studies is the only evidence of medieval architecture in the territory of Reggio Calabria. Numéro de notice : A2018-594 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-018-0231-5 Date de publication en ligne : 07/07/2018 En ligne : https://doi.org/10.1007/s12518-018-0231-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92518
in Applied geomatics > vol 10 n° 4 (December 2018) . - pp 569 - 578[article]GPS precise point positioning for UAV photogrammetry / Ben Grayson in Photogrammetric record, vol 33 n° 164 (December 2018)
[article]
Titre : GPS precise point positioning for UAV photogrammetry Type de document : Article/Communication Auteurs : Ben Grayson, Auteur ; Nigel Penna, Auteur ; Jon P. Mills, Auteur ; Darion S. Grant, Auteur Année de publication : 2018 Article en page(s) : pp 427 - 447 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] compensation par faisceaux
[Termes IGN] géoréférencement direct
[Termes IGN] image captée par drone
[Termes IGN] positionnement ponctuel précis
[Termes IGN] structure-from-motionRésumé : (Auteur) The use of Global Positioning System (GPS) precise point positioning (PPP) on a fixed‐wing unmanned aerial vehicle (UAV) is demonstrated for photogrammetric mapping at accuracies of centimetres in planimetry and about a decimetre in height, from flights of 25 to 30 minutes in duration. The GPS PPP estimated camera station positions are used to constrain estimates of image positions in the photogrammetric bundle block adjustment, as with relative GPS positioning. GPS PPP alleviates all spatial operating constraints associated with the installation and the use of ground control points, a local ground GPS reference station or the need to operate within the bounds of a permanent GPS reference station network. This simplifies operational logistics and enables large‐scale photogrammetric mapping from UAVs in even the most remote and challenging geographic locations. Numéro de notice : A2018-621 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12259 Date de publication en ligne : 05/11/2018 En ligne : https://doi.org/10.1111/phor.12259 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92865
in Photogrammetric record > vol 33 n° 164 (December 2018) . - pp 427 - 447[article]Relevé de la grotte glacée de Cenote Abyss dans les Dolomites / Farouk Kadded in XYZ, n° 157 (décembre 2018 - février 2019)PermalinkRobust vehicle detection in aerial images using bag-of-words and orientation aware scanning / Hailing Zhou in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkAerial data acquisition for a digital railway / James Dunthorne in GIM international, vol 32 n° 4 (July - August 2018)PermalinkAltamétris : des drones et des rails / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)PermalinkDrones et SIG / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)PermalinkSecond iteration of photogrammetric processing to refine image orientation with improved tie-points / Truong Giang Nguyen in Sensors, vol 18 n° 7 (July 2018)PermalinkUsing UAVs for map creation and updating: A case study in Rwanda / Mila Koeva in Survey review, vol 50 n° 361 (July 2018)PermalinkPermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkDéveloppement d'un outil de manipulation optimisée de rasters volumineux / Amaury Zarzelli (2018)Permalink