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Structure from motion for complex image sets / Mario Michelini in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 140 - 152 Titre : Structure from motion for complex image sets Type de document : Article/Communication Auteurs : Mario Michelini, Auteur ; Helmut Mayer, Auteur Année de publication : 2020 Article en page(s) : pp 140 - 152 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] arbre aléatoire minimum [Termes descripteurs IGN] chambre de prise de vue numérique [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] étalonnage d'instrument [Termes descripteurs IGN] fusion de données multisource [Termes descripteurs IGN] itération [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] orientation [Termes descripteurs IGN] reconstruction 3D [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] structure-from-motion Résumé : (auteur) This paper presents an approach for Structure from Motion (SfM) for unorganized complex image sets. To achieve high accuracy and robustness, image triplets are employed and an (approximate) internal camera calibration is assumed to be known. The complexity of an image set is determined by the camera configurations which may include wide as well as weak baselines. Wide baselines occur for instance when terrestrial images and images from small Unmanned Aerial Systems (UAS) are combined. The resulting large (geometric/radiometric) distortions between images make image matching difficult possibly leading to an incomplete result. Weak baselines mean an insufficient distance between cameras compared to the distance of the observed scene and give rise to critical camera configurations. Inappropriate handling of such configurations may lead to various problems in triangulation-based SfM up to total failure. The focus of our approach lies on a complete linking of images even in case of wide or weak baselines. We do not rely on any additional information such as camera configurations, Global Positioning System (GPS) or an Inertial Navigation System (INS). As basis for generating suitable triplets to link the images, an iterative graph-based method is employed formulating image linking as the search for a terminal Steiner minimum tree in the line graph. SIFT (Lowe, 2004) descriptors are embedded into Hamming space for fast image similarity ranking. This is employed to limit the number of pairs to be geometrically verified by a computationally and more complex wide baseline matching method (Mayer et al., 2012). Critical camera configurations which are not suitable for geometric verification are detected by means of classification (Michelini and Mayer, 2019). Additionally, we propose a graph-based approach for the optimization of the hierarchical merging of triplets to efficiently generate larger image subsets. By this means, a complete, 3D reconstruction of the scene is obtained. Experiments demonstrate that the approach is able to produce reliable orientation for large image sets comprising wide as well as weak baseline configurations. Numéro de notice : A2020-355 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.020 date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95242 [article]

Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 7 ([15/05/2020])  

Public [article]  inGeocarto international > vol 35 n° 7 [15/05/2020] . - pp 687 - 699 Titre : Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry Type de document : Article/Communication Auteurs : Maria Luz Gil-Docampo, Auteur ; Marcos Arza-García, Auteur ; Juan Ortiz-Sanz, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 687 - 699 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] acquisition d'images [Termes descripteurs IGN] agronomie [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] photogrammétrie aérienne [Termes descripteurs IGN] sol arable [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) Methods of estimating the total amount of above-ground biomass (AGB) in crop fields are generally based on labourious, random, and destructive in situ sampling. This study proposes a methodology for estimating herbaceous crop biomass using conventional optical cameras and structure from motion (SfM) photogrammetry. The proposed method is based on the determination of volumes according to the difference between a digital terrain model (DTM) and digital surface model (DSM) of vegetative cover. A density factor was calibrated based on a subset of destructive random samples to relate the volume and biomass and efficiently quantify the total AGB. In all cases, RMSE Z values less than 0.23 m were obtained for the DTM-DSM coupling. Biomass field data confirmed the goodness of fit of the yield-biomass estimation (R2=0.88 and 1.12 kg/ha) mainly in plots with uniform vegetation coverage. Furthermore, the method was demonstrated to be scalable to multiple platform types and sensors. Numéro de notice : A2020-186 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1552322 date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1552322 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94993 [article]

Geomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 5 (May 2020) . - pp 189 - 198 Titre : Geomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) Type de document : Article/Communication Auteurs : Stéphane Bertin, Auteur ; Benjamin Levy, Auteur ; Trevor Gee, Auteur ; Patrice Delmas, Auteur Année de publication : 2020 Article en page(s) : pp 189 - 198 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] géoréférencement direct [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] Nouvelle-Zélande [Termes descripteurs IGN] plage [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) Unmanned aerial systems (UAS) and structure-from-motion photogrammetry are transforming the way we produce topo- graphic data, with applications covering many disciplines in the geosciences, including coastal studies. To overcome limitations of ground control points (GCPs), we evaluate direct georeferencing (DG) of consumer UAS imagery for the cost-effective measurement of beach topography. Using DG, camera positions determined with on-board instruments provide air control points for photogrammetry, obviating the need for presurveyed GCPs. We validate the approach at Orewa Beach, New Zealand, achieving vertical accuracies similar to light detection and ranging ( Numéro de notice : A2020-187 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.5.289 date de publication en ligne : 01/05/2020 En ligne : https://doi.org/10.14358/PERS.86.5.289 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95037 [article]

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Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 163 (May 2020) . - pp 171 - 186 Titre : Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images Type de document : Article/Communication Auteurs : Zhen Guan, Auteur ; Amr Abd-Elrahman, Auteur ; Zhen Fan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 171 - 186 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] canopée [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] structure-from-motion Résumé : (auteur) Quantifying canopy biophysical parameters is critical to agricultural research and farm management. In this study, strawberry dry biomass and leaf area were modeled statistically using high spatial and temporal resolution imagery. A mobile field data acquisition system was used to acquire thousands of very high resolution (~0.5 mm) close-range images seven times throughout the strawberry growing season. Ortho-mosaics and dense point clouds were generated through Structure from Motion (SfM) and used in Object-Based Image Analysis (OBIA) at the sub-leaf level to extract canopy structure variables such as planimetric canopy area, canopy average height, and canopy smoothness metric. Regression analysis was carried out using these image-derived canopy variables as predictors to model leaf area ( = 0.79; ten-fold cross-validation RMSE = 0.056 m2) and dry biomass ( = 0.84; ten-fold cross-validation RMSE = 7.72 g) obtained through destructive measurements. Results indicate consistent predictive power through the season and across 17 strawberry genotypes. The study showed that the canopy smoothness metric developed in this study as an indicator of canopy density could complement other variables (planimetric canopy area, canopy average height) that describe canopy geometric properties. Numéro de notice : A2020-139 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.021 date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94757 [article]

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Efficient match pair selection for oblique UAV images based on adaptive vocabulary tree / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 161 (March 2020) . - pp 61 - 75 Titre : Efficient match pair selection for oblique UAV images based on adaptive vocabulary tree Type de document : Article/Communication Auteurs : San Jiang, Auteur ; Wanshou Jiang, Auteur Année de publication : 2020 Article en page(s) : pp 61 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie [Termes descripteurs IGN] analyse des correspondances [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] image aérienne oblique [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] photogrammétrie aérienne [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] structure-from-motion Résumé : (Auteur) The primary contribution of this paper is an efficient match pair selection method for oblique unmanned aerial vehicle (UAV) images. First, high overlap degrees and spatial resolutions cause image and feature redundancies in vocabulary tree building and image indexing. To cope with this issue, an image selection strategy and a feature selection strategy are designed to decrease the total number of features. Second, by analysing the distribution of the similarity scores, an adaptive threshold selection method is implemented to determine the number of candidate match pairs for each query image, and it avoids the disadvantages of the fixed number and fixed proportion methods. Then, an algorithm, termed AVT-Expansion, is proposed for the match pair selection and simplification where the initial match pairs are first selected by using the adaptive vocabulary tree (AVT). To simplify the initial match pairs, the AVT method is integrated with our previous MST-Expansion algorithm, which is used to extract a match graph by analysing the image topological connection network. Finally, the proposed method is verified using three UAV datasets captured with different oblique multi-camera systems. Experimental results demonstrate that the efficiency of the vocabulary tree building is improved, with speed-up ratios ranging from 14 to 16, and that high image retrieval precision values are obtained for the three datasets. For match pair selection of oblique UAV images, the proposed method is an efficient solution. Numéro de notice : A2020-062 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.013 date de publication en ligne : 15/01/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.013 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94578 [article]

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Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering / Shangpeng Sun in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

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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)  

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Streambank topography: an accuracy assessment of UAV-based and traditional 3D reconstructions / Benjamin U. Meinen in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)  

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

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Application of photogrammetry to generate quantitative geobody data in ephemeral fluvial systems / Charlotte L. Priddy in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Innovative techniques of photogrammetry for 3D modeling / Vicenzo Barrile in Applied geomatics, Vol 11 n° 4 (December 2019)  

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A low‐cost open‐source workflow to generate georeferenced 3D SfM photogrammetric models of rocky outcrops / Laurent Froideval in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Pré-localisation des données pour la modélisation 3D de tunnels : développements et évaluations / Christophe Heinkelé in Revue Française de Photogrammétrie et de Télédétection, n° 221 (novembre 2019)

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Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)  

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