dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We would like to thank  Gilles Pagès  from the  Sorbonne university  for a valuable discussion on the Itô calculus of section 4. Figure 4. Color map of u in (0, 2. 5) × (-3, 2) when the standard deviation is (from left to right) µ = [0. 01,0. 125, 0. 25, 0. 5].
Cet article présente une étude comparative entre différent logiciels de photogrammétrie capables de traiter automatiquement plusieurs images pour générer un nuage de points dense dans le domaine industriel. Dans le cadre d'un projet mené dans le l'entreprise Urbica 3D Laser Scanning Survey, quatre jeux de données industrielles ont été réalisés en utilisant les solutions photogrammétriques suivantes : PhotoScan, Pix4DMapper Pro, RealityCapture, MicMac, ReCap Photo et ContextCapture. Chaque jeu de données présente un nombre varié d'images, de résolutions et d'objets d'intérêt de différents niveaux de complexité industrielle. L'évaluation était basée sur trois critères principaux : la précision de l'orientation de l'image, la qualité visuelle et la précision géométrique du nuage de points dense 3D et les différentes caractéristiques du logiciel telles que le temps de traitement et la variabilité des produits de sortie.
The ongoing spread of this technique has led to more diversified software solution. Nearly a hundred-software are regularly updated  (Heno & Chandelier, 2014). However, choosing the right software to meet the required endpoints remains a challenge. Among these varieties of solutions, it is significantly important to determine the optimal ones for the generation of point cloud in industrial sites. The performance of six photogrammetry solutions (Agisoft PhotoScan, Pix4D Pix4DMapper Pro, Capturing Reality RealityCapture, MicMac, ReCap Photo and ContextCapture) which are commonly used in archaeology and aerial photogrammetry were evaluated in industrial environment. Four different industrial data sets were carried out as part of a project conducted in Urbica 3D Laser Scanning Survey Company 1.
Numerous software evaluation studies are available in the literature  (Nex, et al. , 2015) ,  (Knapitsh, et al. , 2017) ,  (Gini, et al. , 2013 ), (Pierrot-desseilligny, et al. , 2011) ,  (Mendes, et al. , 2015) ,  (Alidoost & Arefi, 2017) ,  (Murtiyoso, et al. , 2018). In most cases, the main objective of these evaluation papers was to compare software which are commonly used in archaeology field. Therefore, in this paper, the analysis was focused on close-range photogrammetry software in industrial field. The evaluation was carried out using the following 6 software: ContextCapture: is a photogrammetry software developed by the technological software company Acute3D which became part of the end-to-end Reality Modeling solutions of the american software company Bentley Systems since 2015.
It is available as a standalone desktop or cluster software solution and includes tilling mechanism which allows to handle terabytes of input imagery. This 3D photogrammetry solution is characterized by its capacity to automatically generate 3D meshes with level-of-detail and paging directly with several leading 3D GIS software. RealityCapture: the software RealityCapture (also known as RC) of the Slovakian company Capturing Reality is a stand-alone commercial photogrammetry program based on Structure-from-Motion (SfM), which creates 3D models out of terrestrial/aerial images or laser scans. It is used in different fields such as cultural heritage, gaming, virtual reality and surveying. Characterized by its parallel data processing and the possibility of direct integration of laser scanning point clouds.
Data sets and image sensors description Two Digital Single-Lens Reflex (DSLRs) cameras (Nikon D610 and D810) were used to acquire 4 data sets (overview in Table  1 ). Both cameras have full frame CMOS sensor with a 5. 984-µm pixel size and 35-mm focal length for Nikon D610, and 4. 8859-µm pixel size with 24-mm focal length for Nikon D810. An overview of the technical characteristics of used cameras can be found in Table  3. Nikon D610 was used to acquire images of 3 data sets. Dataset-1 is a test bench established during my internship with Urbica 3D Laser Scanning Survey Company in Paris. It is a set of pipes with different shapes, sizes and color of paintings that are commonly used in industrial sites. A total of 90 images were taken with a Ground Sampling Distance (GSD) up to 0. 3 mm/pix.
Dataset-2 and Dataset-3, were acquired as part of a project aiming to generate 3D model of a ship engine overhaul factory at Saint-Nazaire bay area in France. Dataset-2 presents a complex set of indoor industrial pumps, 157 photos were taken to cover this area with a GSD up to 0. 5 mm/pix. Whereas, Dataset-3 presents a set of electrical boxes where 73 photos were taken with a GSD up 0. 8 mm/pix. The images of 3 data sets were saved in JPEG format with low compression. Regarding Dataset-4, it was recorded using Nikon D810 DSLR camera. It was the similar test bench used in Dataset-1; however, we added a set of 12 calibrated scale bars and a set of 10-coded targets. Scale bars were designed by Cultural Heritage Imaging 2  (CHI) Corporation. They were provided in several sizes with printed targets separated by known distance and calibrated to 1/10 th mm.
, 2011). Additionally, for unbiased comparison and for the sake of consistency, all datasets have been processed with the same computer. An overview of computer technical characteristics are summarized in Table  1. Processor : Intel® Core™ i7-3770 CPU @ 3. 40GHz RAM : 32 Go Operating system : Windows © 7 64bits Graphic Card : Nvidia Quadro K4000 -4GB   (Remondino & Fraser, 2006). Most of software use the auto calibration (i. e. self-calibration) approach in order to estimate the intrinsic camera parameters. In this paper, the same parameters were computed using different software. The calibration parameters could be used as variables in the comparison study, however due to the large number of possible correlations between them performing a direct comparison is complex. Thus, it is necessary to compare the effect of the aforementioned parameters on the accuracy of the 3D restitution.
Dataset-4 was designed to assess the orientation step of each software package; a graphical illustration of the conducted experiment is shown in Table  2. In this data set, 12 calibrated bars were used where the distance between the target centers is well defined 1/10 th mm (see section 4). Three bars were employed for scaling, and the remaining ones as control bars. The alignment of images was performed by each software and the internal orientation parameters were calculated. The tie point extraction phase was performed forcing the same number of extracted Keypoint (40,000) and the same image resolution (full size). In addition, Free-network BA approach was adopted. For Free-network BA we used "Tapas" with the classical Brown's parameters lens camera model "RadialBasic".
Orientation results First re-projection errors of automatic extracted tie points were examined. Whereby each software calculate the projection of tie points from image space towards field space at first, then re-project the pseudo intersection towards the image and compute the error. Formally, mean re-projection errors of less than one pixel is acceptable, whereas above 1 pix results in a noisier dense reconstruction. Subsequently, the accuracy of the alignment was assessed based on scale bars. The mean re-projection errors of most software was 0. 56 ± 0. 1 pix, as shown in Fig. 2. The best result was recorded with RealityCapture 0. 3 pix. Furthermore, ReCap Photo software did not reveal the necessary information about the internal orientation settings and the evaluation of outcomes was not possible.
Thus, this software was excluded from the study. Afterward, the accuracy of the orientation was evaluated by estimating measured distance of the control bars. Results are summarized in Table  4  and Fig. 2. PhotoScan software displayed a root mean square error of 0. 07 mm, which represents the best accuracy value. The highest error was recorded with Pix4DMapper software. It is important to underline that the coded targets exhibited on the control bars were fully detected automatically only with PhotoScan and RealityCapture whereas for the other software, manual method was adopted. Hence, presented results introduce a new parameter which is the precision of targets marking.
Dense point clouds assessment In order to apply same settings, the resulting dense point clouds was considered as the final output of each software. Visual assessment between different generated point cloud using various photogrammetric software was carried out on different benchmark data set (Table  2 ). Then, to assess the edge sharpness and the geometric accuracy, 3D-templates (surfaces, cylinders) were adjusted to the point cloud. The distance between point cloud and geometric shapes was evaluated. While Dataset 3 electrical boxes' were used as test element for surface adjustment, Dataset 2 cylinders' were used for cylinder adjustment. A graphical representation of these templates is shown in Fig. 1. It is worth mentioning that tests using ReCap Photo and ContextCapture did not provide access to the results of the digital image matching, being it fused with the meshing step.
Parameters of Digital Image Matching The same settings were used to generate dense point clouds. With PhtoScan, both "high" and "Mild filtering depth map" options were chosen. With RealityCapture we used the "high model" parameter with image downscale factor 1. Regarding Pix4DMapper we set up the image scale to original image size and the point density to "High". As for MicMac  (Pierrotdeseilligny & Paparodits, 2006) , two modules were used: C3DC Statue and C3DC BigMac. The evaluated point clouds were raw data without any filtering or manual post-processing.
Dense point cloud evaluation results First, we conducted visual quality assessment. The point cloud generated by Pix4DMapper led to locally noisy point clouds especially on uniform surfaces and homogenous textured feature as illustrated in Fig. 3. Regarding the Cylinder adjustment, the overall root mean square error was 0. 85 mm for PhotoScan and 1. 09 mm for RealityCapture. In contrast, the highest error was registered with Pix4DMapper 2. 73 mm for Plan adjustment and 3. 37 mm for Cylinder adjustment. Furthermore, a significant difference in the generated point densities that fits plan and cylinder was registered (Fig. 6 7 ). The highest level of points was recorded with PhotoScan and the lowest with MicMac and Pix4D. Likewise, the total number of generated points by PhotoScan in different data sets was higher than other software, the histogram in Figure  8  reports the density of generated point cloud per data set.
Software features' comparison The processing stage in both orientation and image dense matching was resource and time consuming. We used the same computer to process all data sets. In addition, we enabled the use of GPU option with PhotoScan, RealityCapture and Pix4DMapper. We noticed that commercial software were able to optimize the processing time. A significant processing speed was registered with RealityCapture, controversy to MicMac where the highest processing time was recorded. Histogram in Figure  9   The web solution ReCap Photo is limited in image input format (only JPEG). Moreover, it does not provide parameters for users. Therefore, the main drawback of this solution is the low reliability of the procedure and the lack of accuracy and metrics in results.
Note on orientation and reconstruction algorithms Due to commercial consideration, scarce information was provided about commercial software. With PhotoScan, the first step consists of image alignment regrouping the interior and exterior parameters estimation. The interior orientation covers the estimation of the following parameters: focal length, principal point location, three radial and two tangential distortion coefficients. To do this, PhotoScan use an improved version of SIFT to detect image feature points then perform the BA  (Chiabrando, et al. , 2015). The resulting data is a sparse 3D point cloud corresponding to the locations of the estimated feature points. In the second step, a dense multi-view stereo reconstruction on the aligned images is applied. According to Remondino's paper  (Remondino, et al.
, 2014) , the implemented imagematching algorithm appears to be a Semi-Global Matching reconstruction method (SGM)  (Hirschmüller, 2008) ,  (Hirschmüller, 2005) ,  (James, et al. , 2017). Like PhotoScan, there is reference limitation about the matching algorithms used by RealityCapture. Nevertheless, the implemented image-matching algorithm seems to be a local reconstruction method, a variant of patch match belief propagation approach  (Besse, et al. , 2013). For the orientation phase, MicMac offers two modules Pastis and Apero. The former is performed under Tapioca command in order to generate and match tie points. This module use an improved version of SIFT called SIFT ++ (Pierrot Deseilligny & Clery, 2011),  (Chiabrando, et al. , 2015). "Apero" module which is found under "Tapas" command, performs the camera calibration and the Free-network BA.
MicMac also offer the possibility to perform the BBA under Campari module. Subsequently, a dense image matching for surface reconstruction is performed with MicMac module  (Pierrot Deseilligny & Paparoditis, 2006) , under C3DC interfaces. Micmac performs different approaches of image matching where the user can choose between two different processing strategies, called "image" and "terrain geometries". With the former strategy, the user selects a set of master images for the correlation procedure, then for each 3D point candidate a patch in the master image is identified and projected to all the neighboring images and a global similarity is derived. On the other hand, with "terrain" strategy, a voxel is defined according to the block size and the camera-to-object distance then every 3D point candidate is back-projected onto images and global similarity is derived.
Additionally, in each data set the same parameters were adopted for all software. The assessment of image orientation was based on the re-projection error and the root mean square error (rmse) of 12 calibrated scale bars estimated distances. According to the achieved results, the mean re-projection errors of most software was 0. 5 ± 0. 2 pix. The best performance was recorded with RealityCapture: 0. 3 pix. However, there was differences in the rmse of estimated scale bars' distances. PhotoScan and Reality Capture software displayed a root mean square error of 0. 1 mm, which represents the best accuracy value. The highest error was recorded with Pix4DMapper software. ReCap Photo, which is a web solution, did not reveal the necessary information about the internal orientation settings. The evaluation of outcomes was not possible, thus this software was excluded from the study.
Based on the results of dense point cloud assessment a significant difference was registered. The total number of generated points by PhotoScan was higher than any other software. In addition, the visual qualities and the accuracies of point clouds generated by RealityCapture and PhotoScan were very close to each other in different types of data set and higher than the accuracy of point cloud generated by other software. However, RealityCapture provided better geometric details. Additionally, point clouds generated by Pix4DMapper and MicMac led to locally noisy results especially on uniform surfaces. ContextCapture software does not provide access to the results of the digital image matching, being it fused with the meshing step. Concerning software features, commercial software had a fast processing speed.
For instance, RealityCapture recorded the shortest processing time opposing to MicMac. The latest has a large number of parameters and no graphical interface unlike commercial software which does not display many parameters for the user to choose. This can be seen as advantage (it is easy to use) but also as a drawback since the user does not have a lot of options. The preselected data sets allowed us to evaluate the performance of different software solution in industrial filed. The aim was not to declare a winner, but to suggest a solution to the company in order to update and complete the 3D point cloud generated by TLS. At the present time, we suggest RealityCapture solution as it showed optimal results in image orientation accuracy and the quality of generated dense point clouds in term of sharpness and exhaustiveness.
-Et surtout, lassés d'attendre, beaucoup d'éditeurs de logiciels techniques ont développé des interfaces sur mesure (les « Plug-In ») en se liant à un éditeur major. L'utilisateur devient dépendant d'un éditeur. C'est contraire à l'objectif d'un standard d'échange mondial des données, et interdit l'utilisation d'une maquette numérique unique. Le BIM induit également une révolution des pratiques pour passer d'une ingénierie « séquentielle » à « collaborative ». Par ailleurs, le BIM n'est pas qu'une simple représentation géométrique ou base de données : il se décline en 4D, 5D, 6D, 7D 11. Il n'est pas limité en superficie, qui va de la parcelle (BIM) à l'agglomération (CIM 12 ) et au territoire (TIM 13 ). D'où la nécessité des « conventions BIM » : protocole d'échanges décrivant les procédures collaboratives supports en apparence d'interopérabilité.
Acknowledgements This work was financially supported by the  JSPS   Grant-in-Aid for Scientific Research (B)  (No. 19H02769 , T. S. ; No. 20H02792 , T. I. ),  JSPS   Grant-in-Aid for Young Scientists  (No. 18K14268 , T. I. ), Photo-excitonix Project ( Hokkaido University , T. S. ),  Iketani Science and Technology Foundation  (T. I. ),  Asahi Glass Foundation  (T. I. ),  Toyota Riken  (T. I. ) and  Polynat Carnot Institute  (No. 16-CARN-025-01 , R. B. ). This work was partly performed under the approval of the  Photon Factory Program Advisory Committee  (Proposal No. 2017G589  and  2019G579 ). T. I. gratefully acknowledges the  Nanotech CUPAL NRP program.
Lorsque le nombre d'images utilisées pour reconstruire le modèle est élevé, une recherche exhaustive de tous les correspondants possibles entre toutes les images entraîne rapidement des coûts prohibitifs en termes de temps de calcul et de ressource mémoire. Il est donc nécessaire de limiter les appariements aux quelques images qui ont effectivement un recouvrement entre elles. En fonction de l'information disponible sur les séries d'images obtenues, deux situations se présentent  (Havlena, 2012)  : aucune information d'ordonnancement n'est disponible pour les images (unordered datasets) ou les images peuvent être disposées dans un certain ordre grâce à une information spatiale ou séquentielle (ordered datasets). Dans la première situation, la plus défavorable, il n'existe aucune information spatiale ou séquentielle permettant de situer les images les unes par rapport aux autres.
Pré-localisation par points homologues La première méthode de localisation consiste à calculer des points d'intérêt entre deux images successives de la séquence, puis à les mettre en correspondance en associant les descripteurs extraits. Nous cherchons à estimer une translation selon un seul axe entre 2 poses, c'est pourquoi il n'est pas nécessaire de chercher un grand nombre de points homologues. Une fois une centaine de points appariés, la disparité globale entre images, dM peut être estimée comme la moyenne des inter-distances entre points homologues. En pratique, il est plus robuste de considérer la médiane des interdistances. Pour ce qui est des outils, nous utilisons le logiciel MicMac  (Rupnik et al. , 2017)  et les points homologues sont extraits à l'aide de Sift++. A faible résolution, cette extraction est très rapide d'une image à l'autre, étant donné que l'on peut utiliser le caractère séquentiel des images.
Ces tronçons sont traités indépendamment et agglomérés par la suite entre eux. Cette méthode permet de paralléliser les calculs photogrammétriques sur l'ensemble du tunnel. De cette manière, nous avons élaboré des modèles 3D de différents ouvrages en utilisant les logiciels MicMac  (Rupnik et al. , 2017)  ou Photoscan\metashape 2. Pour ce faire, le regroupement des images propres à chaque tronçon a été réalisé de manière automatique à partir de leur abscisse curviligne, donnée par la méthode proposée. Les images sélectionnées sont celles qui présentent le meilleur recouvrement possible entre elles en évitant les redondances dues aux multiples passages dans le tunnel. L'objectif étant de reconstruire la surface de la paroi du tunnel, il est inutile dans cette étape d'accumuler des images similaires issues de passages différents, car cela alourdit le calcul de toutes les corrélations locales entre les images, et n'améliore pas nécessairement le résultat final.
Acknowledgements None of this work would have existed without inspiring discussions with  Y. Couder  and  E. Fort , nor without their kind encouragement. The insightful remarks and poised skepticism of  A. P. Petroff  and  P. Szymczak  helped us tremendously. We are grateful to  A. Lazarus ,  S. Protière ,  S. Perrard ,  M. Labousse ,  D. H. Rothman ,  F. Métivier ,  J. Neufeld ,  M. T. Biamonte ,  A. Abramian  and  A. Guérin  for many illuminating and stimulating discussions.
Acknowledgments The authors would like to acknowledge Airbus helicopters,  Safran ,  Framatome and Cetim  for their financial support. M. Cici  and  H. Pascal  from  Enise  are thanked for their kind support on machining samples and XRD analysis. Finally, authors acknowledge  M. Mondon  from  Mines Saint Etienne (Armines ) for help on sample preparation and SEM observations.
Dis-moi à quelle vitesse tu te formes, je te dirais si tu es. » « Dis-moi où tu te formes, je te dirais qui tu es. » De ce fait, la description cinétique de l'équilibre chimique permet d'atteindre des états (molécule, Les fondements utilisés dans le modèle cinétique de l'équilibre microscopique présenté dans cette étude sont issus de deux ouvrages de thermodynamique écrits en langue française : Eléments de thermodynamique statistiques15 (1963), d'Adolphe Pacault et Thermodynamique, fondements et applications 4 (2001) de José-Philippe Pérez. La très grande clarté de ces deux ouvrages permet d'accéder sûrement à la connaissance des fondements de la thermodynamique à l'équilibre et de la physique statistique. L'accès à des ouvrages récents et anciens et à des données expérimentales thermodynamiques a été possible grâce à l'accès ouvert de ressources numériques du World Wide Web, nous remercions le National Institute of Standards and Technology, la Dortmund Data Bank, la Bibliothèque Nationale de France pour l'accès Gallica aux fonds anciens et Ressource Canada.
« Dis-moi à quelle vitesse tu te formes, je te dirais si tu es. » « Dis-moi où tu te formes, je te dirais qui tu es. » De ce fait, la description cinétique de l'équilibre chimique permet d'atteindre des états (molécule, Les fondements utilisés dans le modèle cinétique de l'équilibre microscopique présenté dans cette étude sont issus de deux ouvrages de thermodynamique écrits en langue française : Eléments de thermodynamique statistiques15 (1963), d'Adolphe Pacault et Thermodynamique, fondements et applications 4 (2001) de José-Philippe Pérez. La très grande clarté de ces deux ouvrages permet d'accéder sûrement à la connaissance des fondements de la thermodynamique à l'équilibre et de la physique statistique. L'accès à des ouvrages récents et anciens et à des données expérimentales thermodynamiques a été possible grâce à l'accès ouvert de ressources numériques du World Wide Web, nous remercions le National Institute of Standards and Technology, la Dortmund Data Bank, la Bibliothèque Nationale de France pour l'accès Gallica aux fonds anciens et Ressource Canada.