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Low-cost warning system for the monitoring of the Corinth Canal / George Hloupis in Applied geomatics, vol 9 n° 4 (December 2017)
[article]
Titre : Low-cost warning system for the monitoring of the Corinth Canal Type de document : Article/Communication Auteurs : George Hloupis, Auteur ; Vassilis Pagounis, Auteur ; Maria Tsakiri-Strati, Auteur ; George Doxastakis, Auteur ; Vangelis Zacharis, Auteur Année de publication : 2017 Article en page(s) : pp 263 - 277 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] accéléromètre
[Termes IGN] canal
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Grèce
[Termes IGN] gyroscope
[Termes IGN] microsystème électromécanique
[Termes IGN] réseau de capteurs
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) This paper presents an in-house developed low-cost triggering design using wireless sensor network (WSN) nodes. A set of corresponding microelectromechanical system (MEMS) sensors (accelerometer and gyroscope) are used along with a radio transmission unit and a microprocessor. In conjunction with the WSN, terrestrial laser scanning (TLS) measurements are used. Specifically, the aim of this work is to introduce a low-cost WSN node with verified repeatability that will raise an initial signal for possible slope change which will be further verified by TLS measurements. The paper demonstrates the deployment of the developed design for a 3-month period in the Corinth Canal in Greece and presents indicative results. Numéro de notice : A2017-728 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s12518-017-0196-9 Date de publication en ligne : 17/11/2017 En ligne : https://doi.org/10.1007/s12518-017-0196-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88401
in Applied geomatics > vol 9 n° 4 (December 2017) . - pp 263 - 277[article]Experiences with the QDaedalus system for astrogeodetic determination of deflections of the vertical / Markus Hauk in Survey review, vol 49 n° 355 (October 2017)
[article]
Titre : Experiences with the QDaedalus system for astrogeodetic determination of deflections of the vertical Type de document : Article/Communication Auteurs : Markus Hauk, Auteur ; C. Hirt, Auteur ; C. Ackermann, Auteur Année de publication : 2017 Article en page(s) : pp 294 - 301 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] astronomie de position
[Termes IGN] Bavière (Allemagne)
[Termes IGN] chambre zénithale
[Termes IGN] champ de pesanteur local
[Termes IGN] détecteur à transfert de charge
[Termes IGN] déviation de la verticale
[Termes IGN] tachéomètreRésumé : (Auteur) This paper explores the astrogeodetic deflection of the vertical (VD) determination with a light-weight tachymeter-based measurement system called ‘QDaedalus’ developed at ETH Zurich. A description of the relevant components of the system is given to show the set-up and operation. The measuring process including CCD-tachymeter calibration and the astronomical data processing are summarised. The paper then analyses the achievable accuracy of VDs based on new measurement data acquired in Bavaria over several nights. Our measurements were executed atop a pillar on the roof of the TUM and at six stations in the Bavarian Alps (Estergebirge) with highly accurate VDs from previous digital zenith camera measurements available. Our comparisons indicate an accuracy level of 0.15–0.20 arc-seconds for VDs measured with QDaedalus. As a conclusion, our results show that the QDaedalus system is a promising sensor for accurate local astronomical gravity field surveys when a zenith camera is not available. Numéro de notice : A2017-552 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2016.1171960 En ligne : https://doi.org/10.1080/00396265.2016.1171960 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86613
in Survey review > vol 49 n° 355 (October 2017) . - pp 294 - 301[article]A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data / Guiming Zhang in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)
[article]
Titre : A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data Type de document : Article/Communication Auteurs : Guiming Zhang, Auteur ; A - Xing Zhu, Auteur ; Qunying Huang, Auteur Année de publication : 2017 Article en page(s) : pp 2068 - 2097 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données massives
[Termes IGN] estimation par noyau
[Termes IGN] jeu de données localisées
[Termes IGN] optimisation (mathématiques)
[Termes IGN] processeur graphiqueRésumé : (Auteur) Kernel density estimation (KDE) is a classic approach for spatial point pattern analysis. In many applications, KDE with spatially adaptive bandwidths (adaptive KDE) is preferred over KDE with an invariant bandwidth (fixed KDE). However, bandwidths determination for adaptive KDE is extremely computationally intensive, particularly for point pattern analysis tasks of large problem sizes. This computational challenge impedes the application of adaptive KDE to analyze large point data sets, which are common in this big data era. This article presents a graphics processing units (GPUs)-accelerated adaptive KDE algorithm for efficient spatial point pattern analysis on spatial big data. First, optimizations were designed to reduce the algorithmic complexity of the bandwidth determination algorithm for adaptive KDE. The massively parallel computing resources on GPU were then exploited to further speed up the optimized algorithm. Experimental results demonstrated that the proposed optimizations effectively improved the performance by a factor of tens. Compared to the sequential algorithm and an Open Multiprocessing (OpenMP)-based algorithm leveraging multiple central processing unit cores for adaptive KDE, the GPU-enabled algorithm accelerated point pattern analysis tasks by a factor of hundreds and tens, respectively. Additionally, the GPU-accelerated adaptive KDE algorithm scales reasonably well while increasing the size of data sets. Given the significant acceleration brought by the GPU-enabled adaptive KDE algorithm, point pattern analysis with the adaptive KDE approach on large point data sets can be performed efficiently. Point pattern analysis on spatial big data, computationally prohibitive with the sequential algorithm, can be conducted routinely with the GPU-accelerated algorithm. The GPU-accelerated adaptive KDE approach contributes to the geospatial computational toolbox that facilitates geographic knowledge discovery from spatial big data. Numéro de notice : A2017-509 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1324975 En ligne : http://dx.doi.org/10.1080/13658816.2017.1324975 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86455
in International journal of geographical information science IJGIS > vol 31 n° 9-10 (September - October 2017) . - pp 2068 - 2097[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017051 RAB Revue Centre de documentation En réserve L003 Disponible A new GPU bundle adjustment method for large-scale data / Zhou Shunping ; Xiong Xiaodong ; Junfeng Zhu in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)
[article]
Titre : A new GPU bundle adjustment method for large-scale data Type de document : Article/Communication Auteurs : Zhou Shunping, Auteur ; Xiong Xiaodong, Auteur ; Junfeng Zhu, Auteur Année de publication : 2017 Article en page(s) : pp 633 - 641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] compensation par faisceaux
[Termes IGN] jeu de données
[Termes IGN] méthode du gradient conjugué
[Termes IGN] processeur graphique
[Termes IGN] traitement parallèleRésumé : (Auteur) We developed a fast and effective bundle adjustment method for large-scale datasets. The preconditioned conjugate gradient (PCG) algorithm and GPU parallel computing technology are simultaneously applied to deal with large-scale data and to accelerate the bundle adjustment process. The whole bundle adjustment process is modified to enable parallel computing. The critical optimization on parallel task assignment and GPU memory usage are specified. The proposed method was tested using 10 datasets. The traditional Levenberg Marquardt (LM) method, advanced PCG method, Wu's method and the proposed GPU parallel computing method are all compared and analyzed. Preliminary results have shown that the proposed method can process a large-scale dataset with about 13,000 images in less than three minutes on a common computer with GPU device. The efficiency of the proposed method is about the same with Wu's method while the accuracy is better. Numéro de notice : A2017-609 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.9.633 En ligne : https://doi.org/10.14358/PERS.83.9.633 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86887
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 9 (September 2017) . - pp 633 - 641[article]Implementation of an IMU aided image stacking algorithm in a digital camera for Unmanned Aerial Vehicles / Ahmad Audi in Sensors, Vol 17 n°7 (july 2017)
[article]
Titre : Implementation of an IMU aided image stacking algorithm in a digital camera for Unmanned Aerial Vehicles Type de document : Article/Communication Auteurs : Ahmad Audi , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Christophe Meynard , Auteur ; Christian Thom , Auteur Année de publication : 2017 Projets : 1-Pas de projet / Article en page(s) : n° 1646 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] caméra numérique
[Termes IGN] centrale inertielle
[Termes IGN] drone
[Termes IGN] image captée par drone
[Termes IGN] puceRésumé : (auteur) Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work. Numéro de notice : A2017-892 Affiliation des auteurs : LASTIG LOEMI (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.3390/s17071646 Date de publication en ligne : 18/07/2017 En ligne : https://doi.org/10.3390/s17071646 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91885
in Sensors > Vol 17 n°7 (july 2017) . - n° 1646[article]Automatic GPS ionospheric amplitude and phase scintillation detectors using a machine learning algorithm / Yu Jiao in Inside GNSS, vol 12 n° 3 (May - June 2017)PermalinkChange detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis / Arati Paul in Geocarto international, vol 32 n° 6 (June 2017)PermalinkA parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs / Chen Zhou in Transactions in GIS, vol 21 n° 3 (June 2017)PermalinkImplantation dans le matériel de fonctionnalités temps-réel dans une caméra intelligente ultralégère spécialisée pour la prise de vue aérienne / Ahmad Audi (2017)PermalinkRéalisation d'une caméra photogrammétrique ultralégère et de haute résolution / Olivier Martin in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkThe index array approach and the dual tiled similarity algorithm for UAS hyper-spatial image processing / Lihong Su in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkDistance measure based change detectors for polarimetric SAR imagery / Yonghong Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)PermalinkA simulated annealing algorithm for zoning in planning using parallel computing / Inès Santé in Computers, Environment and Urban Systems, vol 59 (September 2016)PermalinkSpaceborne synthetic aperture radar data focusing on multicore-based architectures / Pasquale Imperatore in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkA bootstrap test for constant coefficients in geographically weighted regression models / Chang-Lin Mei in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)Permalink