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Index-supported pattern matching on tuples of time-dependent values / Fabio Valdés in Geoinformatica, vol 21 n° 3 (July - September 2017)
[article]
Titre : Index-supported pattern matching on tuples of time-dependent values Type de document : Article/Communication Auteurs : Fabio Valdés, Auteur ; Ralf Hartmut Güting, Auteur Année de publication : 2017 Article en page(s) : pp 429 - 458 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] appariement de données localisées
[Termes IGN] appariement de modèles conceptuels de données
[Termes IGN] attribut sémantique
[Termes IGN] base de données orientée objet
[Termes IGN] données géologiques
[Termes IGN] données maillées
[Termes IGN] données spatiotemporelles
[Termes IGN] index spatial
[Termes IGN] objet mobile
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] Rome
[Termes IGN] trace GPS
[Termes IGN] traitement de données localisées
[Termes IGN] transport routierRésumé : (Auteur) Lately, the amount of mobility data recorded by GPS-enabled (and other) devices has increased drastically, entailing the necessity of efficient processing and analysis methods. In many cases, not only the geographic position, but also additional time-dependent information are traced and/or generated, according to the purpose of the evaluation. For example, in the field of animal behavior research, besides the position of the monitored animal, biologists are interested in further data like the altitude or the temperature at every measuring point. Other application domains comprise the names of streets, places of interest, or transportation modes that can be recorded along with the geographic position of a person. In this paper, we present in detail a framework for analyzing datasets with arbitrarily many time-dependent attributes. This can be considered as a major extension of our previous work, a comprehensive framework for pattern matching on symbolic trajectories with index support. For an efficient processing of different data types, a variable number of indexes of four different types that correspond to the data types of the attributes are applied. We demonstrate the expressiveness and efficiency of our approach by querying a real dataset representing taxi trips in Rome and, particularly, with a broad series of experiments using trajectories generated by BerlinMOD combined with geological raster data. Numéro de notice : A2017-377 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0286-6 En ligne : https://doi.org/10.1007/s10707-016-0286-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85809
in Geoinformatica > vol 21 n° 3 (July - September 2017) . - pp 429 - 458[article]Disocclusion of 3D LiDAR point clouds using range images / Pierre Biasutti in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)
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Titre : Disocclusion of 3D LiDAR point clouds using range images Type de document : Article/Communication Auteurs : Pierre Biasutti , Auteur ; Jean-François Aujol, Auteur ; Mathieu Brédif , Auteur ; Aurélie Bugeau, Auteur Année de publication : 2017 Projets : GOTMI / Papadakis, Nicolas Conférence : ISPRS 2017, Workshops HRIGI – CMRT – ISA – EuroCOW 06/06/2017 09/06/2017 Hanovre Allemagne ISPRS OA Annals Article en page(s) : pp 75 - 82 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] objet mobile
[Termes IGN] retouche
[Termes IGN] scène urbaine
[Termes IGN] semis de pointsRésumé : (auteur) This paper proposes a novel framework for the disocclusion of mobile objects in 3D LiDAR scenes aquired via street-based Mobile Mapping Systems (MMS). Most of the existing lines of research tackle this problem directly in the 3D space. This work promotes an alternative approach by using a 2D range image representation of the 3D point cloud, taking advantage of the fact that the problem of disocclusion has been intensively studied in the 2D image processing community over the past decade. First, the point cloud is turned into a 2D range image by exploiting the sensor’s topology. Using the range image, a semi-automatic segmentation procedure based on depth histograms is performed in order to select the occluding object to be removed. A variational image inpainting technique is then used to reconstruct the area occluded by that object. Finally, the range image is unprojected as a 3D point cloud. Experiments on real data prove the effectiveness of this procedure both in terms of accuracy and speed. Numéro de notice : A2017-898 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-1-W1-75-2017 Date de publication en ligne : 30/05/2017 En ligne : https://doi.org/10.5194/isprs-annals-IV-1-W1-75-2017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91913
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-1/W1 (May 2017) . - pp 75 - 82[article]Design principles of a stream-based framework for mobility analysis / Loic Salmon in Geoinformatica, vol 21 n° 2 (April - June 2017)
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Titre : Design principles of a stream-based framework for mobility analysis Type de document : Article/Communication Auteurs : Loic Salmon, Auteur ; Cyril Ray, Auteur Année de publication : 2017 Article en page(s) : pp 237 - 261 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatiale
[Termes IGN] approche holistique
[Termes IGN] cartographie à la volée
[Termes IGN] flux de données
[Termes IGN] gestion de trafic
[Termes IGN] navigation maritime
[Termes IGN] objet mobile
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] système de gestion de flux de données
[Termes IGN] temps réel
[Termes IGN] traitement interactif
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Trajectory analysis is of crucial importance in several fields as social analysis, zoology, climatology or traffic monitoring. Over the last decade, the number of mobile systems and devices recording their positions has grown significantly generating a deluge of spatial and temporal data to analyze. This increasing volume of data raises numerous issues in terms of storage, processing and extraction of information. Previous works considering movement analysis have been mainly oriented towards either archived data processing and mining or continuous handling of incoming streams. The research developed in this paper introduces the design principles of a holistic approach combining real-time processing and archived data analysis to process mobility data “on the fly”. This solution aims to provide better results comparing to both purely offline and online approaches. This research considers distributed data and processing to be more efficient. The design principles are applied to maritime traffic analysis and a few representative examples are introduced to demonstrate the relevance of our approach. Numéro de notice : A2017-070 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0256-z En ligne : http://dx.doi.org/10.1007/s10707-016-0256-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84297
in Geoinformatica > vol 21 n° 2 (April - June 2017) . - pp 237 - 261[article]Distributed processing of big mobility data as spatio-temporal data streams / Zdravko Galić in Geoinformatica, vol 21 n° 2 (April - June 2017)
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Titre : Distributed processing of big mobility data as spatio-temporal data streams Type de document : Article/Communication Auteurs : Zdravko Galić, Auteur ; Emir Mešković, Auteur ; Dario Osmanović, Auteur Année de publication : 2017 Article en page(s) : pp 263 - 291 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données massives
[Termes IGN] données spatiotemporelles
[Termes IGN] environnement de développement
[Termes IGN] flux de données
[Termes IGN] mobilité territoriale
[Termes IGN] mobilité urbaine
[Termes IGN] objet mobile
[Termes IGN] prototype
[Termes IGN] temps réel
[Termes IGN] traitement répartiRésumé : (Auteur) Recent rapid development of wireless communication, mobile computing, global navigation satellite systems (GNSS), and spatially enabled sensors are leading to an exponential growth of available mobility data produced continuously at high speed. Due to these advancements, a new class of monitoring applications has come to the focus, including real-time intelligent transportation systems, traffic monitoring and mobile objects tracking. These new information flow processing (IFP) application domains need to process huge volume of mobility data arriving in the form of continuous data streams from mobile objects. IFP applications are pushing traditional database technologies beyond their limits due to their massively increasing data volumes and demands for real-time processing. Mobility data, i.e. real-time, transient, time-varying sequences of spatio-temporal data items, generated by embedded positioning sensors demonstrates at least two Big Data core features: volume and velocity. Existing distributed data stream management systems (DSMS), real-time computing systems (RTCS) and their processing models are dominantly based on relational paradigm and continuous operator model. Thus, they have rudimentary spatio-temporal capabilities, provide expensive fault recovery requiring either hot replication or long recovery times, and do not handle faults and slow nodes. The framework proposed in this paper is a cornerstone towards efficient real-time managing and monitoring of mobile objects through distributed spatio-temporal streams processing on large clusters. A prototype implementation is rooted in a new stream processing model that overcomes the challenges of current distributed stream processing models and enable seamless integration with batch and interactive processing like MapReduce. Numéro de notice : A2017-069 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0264-z En ligne : http://dx.doi.org/10.1007/s10707-016-0264-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84300
in Geoinformatica > vol 21 n° 2 (April - June 2017) . - pp 263 - 291[article]Panda∗: A generic and scalable framework for predictive spatio-temporal queries / Abdeltawab M. Hendawi in Geoinformatica, vol 21 n° 2 (April - June 2017)
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Titre : Panda∗: A generic and scalable framework for predictive spatio-temporal queries Type de document : Article/Communication Auteurs : Abdeltawab M. Hendawi, Auteur ; Mohamed Ali, Auteur ; Mohamed F. Mokbel, Auteur Année de publication : 2017 Article en page(s) : pp 175 - 208 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] environnement de développement
[Termes IGN] espace euclidien
[Termes IGN] gestion de trafic
[Termes IGN] objet mobile
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] prédiction
[Termes IGN] requête spatiotemporelleRésumé : (Auteur) Predictive spatio-temporal queries are crucial in many applications. Traffic management is an example application, where predictive spatial queries are issued to anticipate jammed areas in advance. Also, location-aware advertising is another example application that targets customers expected to be in the vicinity of a shopping mall in the near future. In this paper, we introduce Panda∗, a generic framework for supporting spatial predictive queries over moving objects in Euclidean spaces. Panda∗ distinguishes itself from previous work in spatial predictive query processing by the following features: (1) Panda∗ is generic in terms of supporting commonly-used types of queries, (e.g., predictive range, KNN, aggregate queries) over stationary points of interests as well as moving objects. (2) Panda∗ employees a prediction function that provides accurate prediction even under the absence or the scarcity of the objects’ historical trajectories. (3) Panda∗ is customizable in the sense that it isolates the prediction calculation from query processing. Hence, it enables the injection and integration of user defined prediction functions within its query processing framework. (4) Panda∗ deals with uncertainties and variabilities in the expected travel time from source to destination in response to incomplete information and/or dynamic changes in the underlying Euclidean space. (5) Panda∗ provides a controllable parameter that trades low latency responses for computational resources. Experimental analysis proves the scalability of Panda∗ in evaluating a massive volume of predictive queries over large numbers of moving objects. Numéro de notice : A2017-068 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0284-8 En ligne : http://dx.doi.org/10.1007/s10707-016-0284-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84295
in Geoinformatica > vol 21 n° 2 (April - June 2017) . - pp 175 - 208[article]Recherche des objets mobiles dans les réseaux routiers : Une approche basée sur l’analyse formelle de concepts / Hafedh Ferchichi in Revue internationale de géomatique, vol 27 n° 2 (avril - juin 2017)PermalinkA virtual globe-based visualization and interactive framework for a small craft navigation assistance system in the near sea / Xinzhu Liu in Journal of Traffic and Transportation Engineering (English Edition), n° (April 2017)PermalinkImage-based target detection and radial velocity estimation methods for multichannel SAR-GMTI / Kei Suwa in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkVisual exploration of movement and event data with interactive time masks / Natalia Andrienko in Visual Informatics, vol 1 n° 1 (March 2017)PermalinkCartographie et interprétation de l'environnement par drone / Martial Sanfourche in Revue Française de Photogrammétrie et de Télédétection, n° 213 - 214 (janvier - avril 2017)PermalinkPermalinkVisual analytics of delays and interaction in movement data / Maximilian Konzack in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)PermalinkComment gérer la sirène de la mobilité ? / Françoise de Blomac in DécryptaGéo le mag, n° 182 (décembre 2016)PermalinkA probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkD'une cartographie de flux à une cartographie du mouvement : aspects sémiologiques / Françoise Bahoken in Cartes & Géomatique, n° 229-230 (septembre 2016 - février 2017)Permalink