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A framework for group converging pattern mining using spatiotemporal trajectories / Bin Zhao in Geoinformatica, vol 24 n° 4 (October 2020)
[article]
Titre : A framework for group converging pattern mining using spatiotemporal trajectories Type de document : Article/Communication Auteurs : Bin Zhao, Auteur ; Xintao Liu, Auteur ; Jinping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 745 - 776 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatio-temporelle
[Termes IGN] base de données d'objets mobiles
[Termes IGN] base de données spatiotemporelles
[Termes IGN] comportement
[Termes IGN] convergence
[Termes IGN] exploration de données géographiques
[Termes IGN] jointure spatiale
[Termes IGN] objet mobile
[Termes IGN] reconnaissance de formesRésumé : (Auteur) A group event such as human and traffic congestion can be very roughly divided into three stages: converging stage before congestion, gathered stage when congestion happens, and dispersing stage that congestion disappears. It is of great interest in modeling and identifying converging behaviors before gathered events actually happen, which helps to proactively predict and handle potential public incidents such as serious stampedes. However, most of existing literature put too much emphasis on the second stage, only a few of them is dedicated to the first stage. In this paper, we propose a novel group pattern, namely converging, which refers to a group of moving objects converging from different directions during a certain period before gathered. To discover efficiently such converging patterns, we develop a framework for converging pattern mining (CPM) by examining how moving objects form clusters and the process of the “cluster containment”. The framework consists of three phases: snapshot cluster discovery phase, cluster containment join phase, and converging detection phase. As cluster containment mining is the key step, we develop three algorithms to discover cluster containment matches: a containment-join-algorithm, called SSCCJ, by using spatial proximity; a signature tree-based cluster-containment-join-algorithm, called STCCJ, which takes advantage of the cluster containment relations and signature techniques to filter enormous unqualified candidates in an efficient and effective way; and third, to keep the advantages of the above algorithms while avoiding their flaws, we further propose a signature quad-tree based cluster-containment-join algorithm, called SQTCCJ, which can identify efficiently matches by considering cluster spatial proximity as well as containment relations simultaneously. To assess the proposed methods, we redefine two evaluation metrics based on the concept of “Precision and Recall” in the field of information retrieval and the characteristics of converging patterns. We also propose a new indicator for measuring the duration of the converging stage in a group event. Finally, the effectiveness of the CPM and the efficiency of the mining algorithms are evaluated using three types of trajectory datasets, and the results show that the SQTCCJ algorithm demonstrates a superior performance. Numéro de notice : A2020-494 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00404-z Date de publication en ligne : 25/04/2020 En ligne : https://doi.org/10.1007/s10707-020-00404-z Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96114
in Geoinformatica > vol 24 n° 4 (October 2020) . - pp 745 - 776[article]Learning high-level features by fusing multi-view representation of MLS point clouds for 3D object recognition in road environments / Zhipeng Luo in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)
[article]
Titre : Learning high-level features by fusing multi-view representation of MLS point clouds for 3D object recognition in road environments Type de document : Article/Communication Auteurs : Zhipeng Luo, Auteur ; Jonathan Li, Auteur ; Zhenlong Xiao, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 44 - 58 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données
[Termes IGN] jointure spatiale
[Termes IGN] objet 3D
[Termes IGN] reconnaissance d'objets
[Termes IGN] représentation multiple
[Termes IGN] réseau neuronal convolutif
[Termes IGN] semis de pointsRésumé : (Auteur) Most existing 3D object recognition methods still suffer from low descriptiveness and weak robustness although remarkable progress has made in 3D computer vision. The major challenge lies in effectively mining high-level 3D shape features. This paper presents a high-level feature learning framework for 3D object recognition through fusing multiple 2D representations of point clouds. The framework has two key components: (1) three discriminative low-level 3D shape descriptors for obtaining multi-view 2D representation of 3D point clouds. These descriptors preserve both local and global spatial relationships of points from different perspectives and build a bridge between 3D point clouds and 2D Convolutional Neural Networks (CNN). (2) A two-stage fusion network, which consists of a deep feature learning module and two fusion modules, for extracting and fusing high-level features. The proposed method was tested on three datasets, one of which is Sydney Urban Objects dataset and the other two were acquired by a mobile laser scanning (MLS) system along urban roads. The results obtained from comprehensive experiments demonstrated that our method is superior to the state-of-the-art methods in descriptiveness, robustness and efficiency. Our method achieves high recognition rates of 94.6%, 93.1% and 74.9% on the above three datasets, respectively. Numéro de notice : A2019-137 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.024 Date de publication en ligne : 16/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.024 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92468
in ISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 44 - 58[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Query rewriting for semantic query optimization in spatial databases / Eduardo Mella in Geoinformatica, vol 23 n° 1 (January 2019)
[article]
Titre : Query rewriting for semantic query optimization in spatial databases Type de document : Article/Communication Auteurs : Eduardo Mella, Auteur ; M. Andrea Rodríguez, Auteur ; Loreto Bravo, Auteur ; Diego Gatica, Auteur Année de publication : 2019 Article en page(s) : pp 79 - 104 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] contrainte d'intégrité
[Termes IGN] jointure spatiale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] programmation par contraintes
[Termes IGN] relation topologique
[Termes IGN] requête (informatique)
[Termes IGN] requête spatiale
[Termes IGN] système de gestion de bases de données orientées objetRésumé : (auteur) Query processing is an important challenge for spatial databases due to the use of complex data types that represent spatial attributes. In particular, due to the cost of spatial joins, several optimization algorithms based on indexing structures exist. The work in this paper proposes a strategy for semantic query optimization of spatial join queries. The strategy detects queries with empty results and rewrites queries to eliminate unnecessary spatial joins or to replace spatial by thematic joins. This is done automatically by analyzing the semantics imposed by the database schema through topological dependencies and topological referential integrity constraints. In this way, the strategy comes to complement current state-of-art algorithms for processing spatial join queries. The experimental evaluation with real data sets shows that the optimization strategy can achieve a decrease in the time cost of a join query using indexing structures in a spatial database management system (SDBMS). Numéro de notice : A2019-224 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-00335-w Date de publication en ligne : 04/01/2019 En ligne : http://dx.doi.org/10.1007/s10707-018-00335-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92623
in Geoinformatica > vol 23 n° 1 (January 2019) . - pp 79 - 104[article]Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules / Yongjiu Feng in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)
[article]
Titre : Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules Type de document : Article/Communication Auteurs : Yongjiu Feng, Auteur Année de publication : 2017 Article en page(s) : pp 1198 - 1219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] algorithme génétique
[Termes IGN] analyse diachronique
[Termes IGN] automate cellulaire
[Termes IGN] base de règles
[Termes IGN] changement d'utilisation du sol
[Termes IGN] données GPS
[Termes IGN] jointure spatiale
[Termes IGN] Kiangsou (Chine)
[Termes IGN] modèle de simulation
[Termes IGN] prédiction
[Termes IGN] régression logistique
[Termes IGN] simulation
[Termes IGN] zone urbaineRésumé : (auteur) A novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development. Numéro de notice : A2017-244 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2017.1287368 En ligne : http://dx.doi.org/10.1080/13658816.2017.1287368 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85180
in International journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017) . - pp 1198 - 1219[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 079-2017031 RAB Revue Centre de documentation En réserve L003 Disponible On reverse-k-nearest-neighbor joins / Tobias Emrich in Geoinformatica, vol 19 n° 2 (April - June 2015)
[article]
Titre : On reverse-k-nearest-neighbor joins Type de document : Article/Communication Auteurs : Tobias Emrich, Auteur ; Hans-Peter Kriege, Auteur ; Peer Kröger, Auteur ; et al., Auteur Année de publication : 2015 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse comparative
[Termes IGN] classification barycentrique
[Termes IGN] espace métrique
[Termes IGN] espace vectoriel
[Termes IGN] jointure spatiale
[Termes IGN] requête (informatique)
[Termes IGN] requête spatiale inverseRésumé : (auteur) A reverse k-nearest neighbour (RkNN) query determines the objects from a database that have the query as one of their k-nearest neighbors. Processing such a query has received plenty of attention in research. However, the effect of running multiple RkNN queries at once (join) or within a short time interval (bulk/group query) has only received little attention so far. In this paper, we analyze different types of RkNN joins and provide a classification of existing RkNN join algorithms. We discuss possible solutions for solving the non-trivial variants of the problem in vector spaces, including self and mutual pruning strategies. Further, we generalize the developed algorithms to general metric spaces. During an extensive performance analysis we provide evaluation results showing the IO and CPU performance of the compared algorithms for a wide range of different setups and suggest appropriate query algorithms for specific scenarios. Numéro de notice : A2015-490 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0215-5 Date de publication en ligne : 23/08/2014 En ligne : https://doi.org/10.1007/s10707-014-0215-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77283
in Geoinformatica > vol 19 n° 2 (April - June 2015)[article]PostGIS : Introduction / Fabien Guerreiro (2015)PermalinkNIBU: An integrated framework for representing the relation among building structure and interior utilities in micro-scale environment / Ihab Hijazi in Geo-spatial Information Science, vol 14 n° 2 (01/06/2011)PermalinkIRSJ : incremental refining spatial joins for interactive queries in GIS / W. Bae in Geoinformatica, vol 14 n° 4 (October 2010)PermalinkLocation-based algorithms for finding sets of corresponding objects over several geo-spatial data sets / E. Safra in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)PermalinkRetrieval of Spatial Join Pattern Instances from Sensor Networks / M.L. Yiu in Geoinformatica, vol 13 n° 1 (March 2009)PermalinkMathématiques pour la modélisation géométrique, la représentation 3D et la synthèse d'images / L. Garnier (2007)PermalinkQuery processing in spatial databases containing obstacles / Jun Zhang in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)PermalinkPermalinkMulti-way distance joins queries in spatial databases / A. Corral in Geoinformatica, vol 8 n° 4 (December 2004)PermalinkPolyline spatial join evaluation using raster approximation / L.G. Azevedo in Geoinformatica, vol 7 n° 4 (December 2003)Permalink