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Novel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud / Jie Yang in Forests, vol 13 n° 10 (October 2022)
Titre : Novel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud Type de document : Article/Communication Auteurs : Jie Yang, Auteur ; Xiaorong Wen, Auteur ; Qiulai Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] branche (arbre)
[Termes IGN] C++
[Termes IGN] Chine
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] itération
[Termes IGN] modélisation de la forêt
[Termes IGN] semis de points
[Termes IGN] squelettisationRésumé : (auteur) More accurate tree models, such as branch skeleton, are needed to acquire forest inventory data. Currently available algorithms for constructing a branch skeleton from a LiDAR point cloud have low accuracy with problems such as irrational connection near trunk bifurcation, excessive central deviation and topological errors. Using the C++ and PCL library, a novel algorithm of the incomplete simulation of tree transmitting water and nutrients (ISTTWN), based on geometric characteristics for tree branch skeleton extraction, was developed in this research. The algorithm is an incomplete simulation of tree transmitting water and nutrients. Improvements were made to improve the time and memory consumption. The result show that the ISTTWN algorithm without any improvements is quite time consuming but has consecutive output. After improvement with iteration, the process is faster and has more detailed output. Breakpoint connection is added to recover continuity. The ISTTWN algorithm with improvements can produce a more accurate skeleton and cost less time than a previous algorithm. The superiority and effectiveness of the method are demonstrated, which provides a reference for the subsequent study of tree modeling and a prospect of application in other fields, such as virtual reality, computer games and movie scenes. Numéro de notice : A2022-835 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13101534 Date de publication en ligne : 17/09/2022 En ligne : https://doi.org/10.3390/f13101534 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102032
in Forests > vol 13 n° 10 (October 2022) . - n° 1534[article]
Titre : An algorithm to assist the robust filter for tightly coupled RTK/INS navigation system Type de document : Article/Communication Auteurs : Zun Niu, Auteur ; Guangchen Li, Auteur ; Fugui Guo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2449 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] C++
[Termes IGN] centrale inertielle
[Termes IGN] erreur de positionnement
[Termes IGN] filtre de Kalman
[Termes IGN] implémentation (informatique)
[Termes IGN] matrice de covariance
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] précision du positionnement
[Termes IGN] rapport signal sur bruit
[Termes IGN] valeur aberranteRésumé : (auteur) The Real-Time Kinematic (RTK) positioning algorithm is a promising positioning technique that can provide real-time centimeter-level positioning precision in GNSS-friendly areas. However, the performance of RTK can degrade in GNSS-hostile areas like urban canyons. The surrounding buildings and trees can reflect and block the Global Navigation Satellite System (GNSS) signals, obstructing GNSS receivers’ ability to maintain signal tracking and exacerbating the multipath effect. A common method to assist RTK is to couple RTK with the Inertial Navigation System (INS). INS can provide accurate short-term relative positioning results. The Extended Kalman Filter (EKF) is usually used to couple RTK with INS, whereas the GNSS outlying observations significantly influence the performance. The Robust Kalman Filter (RKF) is developed to offer resilience against outliers. In this study, we design an algorithm to improve the traditional RKF. We begin by implementing the tightly coupled RTK/INS algorithm and the conventional RKF in C++. We also introduce our specific implementation in detail. Then, we test and analyze the performance of our codes on public datasets. Finally, we propose a novel algorithm to improve RKF and test the improvement. We introduce the Carrier-to-Noise Ratio (CNR) to help detect outliers that should be discarded. The results of the tests show that our new algorithm’s accuracy is improved when compared to the traditional RKF. We also open source the majority of our code, as we find there are few open-source projects for coupled RTK/INS in C++. Researchers can access the codes at our GitHub. Numéro de notice : A2022-401 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs14102449 Date de publication en ligne : 20/05/2022 En ligne : https://doi.org/10.3390/rs14102449 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100704
in Remote sensing > vol 14 n° 10 (May-2 2022) . - n° 2449[article]
Titre : Generic programming in modern C++ for image processing Type de document : Thèse/HDR Auteurs : Michaël Roynard, Auteur ; Thierry Géraud, Directeur de thèse ; Edwin Carlinet, Directeur de thèse Editeur : Paris : Sorbonne Université Année de publication : 2022 Importance : 237 p. Format : 21 x 30 cm Note générale : bibliographie
Doctoral thesis submitted to fufill the requirements for the degree of Doctor of Sorbonne Université with the doctoral speciality of "Software Engineering and Image Processing"Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Langages informatiques
[Termes IGN] C++
[Termes IGN] langage de programmation
[Termes IGN] morphologie mathématique
[Termes IGN] programmation informatique
[Termes IGN] taxinomie
[Termes IGN] traitement d'imageIndex. décimale : THESE Thèses et HDR Résumé : (auteur) C++ is a multi-paradigm language that enables the initiated programmer to set up efficient image processing algorithms. This language strength comes from several aspects. C++ is high-level, which enables developing powerful abstractions and mixing different programming styles to ease the development. At the same time, C++ is low-level and can fully take advantage of the hardware to deliver the best performance. It is also very portable and highly compatible which allows algorithms to be called from high-level, fast-prototyping languages such as Python or Matlab. One of the most fundamental aspects where C++ really shines is generic programming. Generic programming makes it possible to develop and reuse bricks of software on objects (images) of different natures (types) without performance loss. Nevertheless,conciliating the aspects of genericity, efficiency, and simplicity is not trivial. Modern C++ (post-2011) has brought new features that made the language simpler and more powerful. In this thesis, we first explore one particular C++20aspect: the concepts, in order to build a concrete taxonomy of image related types and algorithms. Second, we explore another addition to C++20, ranges (and views), and we apply this design to image processing algorithms and image types in order to solve issues such as how hard it is to customize/tweak image processing algorithms. Finally, we explore possibilities regarding how we can offer a bridge between static (compile-time) generic C++ code and dynamic (runtime) Python code. We offer our own hybrid solution and benchmark its performance as well as discuss what can be done in the future with JIT technologies. Considering those three axes, we will address the issue regarding the way to conciliate generic programming, efficiency and ease of use. Note de contenu : I Context and History of Generic programming
1- Introduction
2- Generic programming (genericity)
II Applying Generic programming for Image processing in the static world
3- Taxonomy for Image Processing: Image types and algorithms
4- Image views
III Bringing Generic programming to the dynamic world
5- A bridge between the static world and the dynamic world
6- Conclusion and continuationNuméro de notice : 24083 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Thèse française Note de thèse : PhD thesis : Software Engineering and Image Processing : Sorbonne Université : 2022 Organisme de stage : EPITA DOI : sans En ligne : https://theses.hal.science/tel-03922670 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102391
Titre : GROOPS: A software toolkit for gravity field recovery and GNSS processing Type de document : Article/Communication Auteurs : Torsten Mayer-Gürr, Auteur ; Saniya Behzadpour, Auteur ; Annette Eicker, Auteur Année de publication : 2021 Article en page(s) : n° 104864 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] C++
[Termes IGN] champ de pesanteur terrestre
[Termes IGN] logiciel libre
[Termes IGN] orbitographie
[Termes IGN] série temporelle
[Termes IGN] traitement de données GNSSRésumé : (auteur) The Gravity Recovery Object Oriented Programming System (GROOPS) is a software toolkit written in C++ that enables the user to perform core geodetic tasks. Key features of the software include gravity field recovery from satellite and terrestrial data, the determination of satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. Next to raw data processing, GROOPS is capable to operate on time series and spatial data to directly analyze and visualize the computed data sets. Most tasks and algorithms are (optionally) parallelized through the Message Passing Interface, thus the software enables a smooth transition from single-CPU desktop computers to large distributed computing environments for resource intensive tasks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of the software is freely available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and step-by-step installation instructions. Numéro de notice : A2021-948 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.cageo.2021.104864 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104864 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99765
in Computers & geosciences > vol 155 (October 2021) . - n° 104864[article]
Titre : The integration of GPS/BDS real-time kinematic positioning and visual–inertial odometry based on smartphones Type de document : Article/Communication Auteurs : Zun Niu, Auteur ; Fugui Guo, Auteur ; Qiangqiang Shuai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 699 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] C++
[Termes IGN] centrale inertielle
[Termes IGN] filtre de Kalman
[Termes IGN] format RINEX
[Termes IGN] odomètre
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] positionnement par BeiDou
[Termes IGN] positionnement par GNSS
[Termes IGN] précision du positionnement
[Termes IGN] programmation informatique
[Termes IGN] robot
[Termes IGN] téléphone intelligent
[Termes IGN] vision par ordinateurRésumé : (auteur) The real-time kinematic positioning technique (RTK) and visual–inertial odometry (VIO) are both promising positioning technologies. However, RTK degrades in GNSS-hostile areas, where global navigation satellite system (GNSS) signals are reflected and blocked, while VIO is affected by long-term drift. The integration of RTK and VIO can improve the accuracy and robustness of positioning. In recent years, smartphones equipped with multiple sensors have become commodities and can provide measurements for integrating RTK and VIO. This paper verifies the feasibility of integrating RTK and VIO using smartphones, and we propose an improved algorithm to integrate RTK and VIO with better performance. We began by developing an Android smartphone application for data collection and then wrote a Python program to convert the data to a robot operating system (ROS) bag. Next, we established two ROS nodes to calculate the RTK results and accomplish the integration. Finally, we conducted experiments in urban areas to assess the integration of RTK and VIO based on smartphones. The results demonstrate that the integration improves the accuracy and robustness of positioning and that our improved algorithm reduces altitude deviation. Our work can aid navigation and positioning research, which is the reason why we open source the majority of the codes at our GitHub. Numéro de notice : A2021-800 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10100699 Date de publication en ligne : 14/10/2021 En ligne : https://doi.org/10.3390/ijgi10100699 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98852
in ISPRS International journal of geo-information > vol 10 n° 10 (October 2021) . - n° 699[article]Machine learning and pose estimation for autonomous robot grasping with collaborative robots / Victor Talbot (2018)
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