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A simplified ICA-based local similarity stereo matching / Suting Chen in The Visual Computer, vol 37 n° 2 (February 2021)  

Public [article]  inThe Visual Computer > vol 37 n° 2 (February 2021) . - pp 411 - 419 Titre : A simplified ICA-based local similarity stereo matching Type de document : Article/Communication Auteurs : Suting Chen, Auteur ; Jinglin Zhang, Auteur ; Meng Jin, Auteur Année de publication : 2021 Article en page(s) : pp 411 - 419 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] analyse en composantes indépendantes [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] similitude Résumé : (auteur) Since the existing stereo matching methods may fail in the regions of non-textures, boundaries and tiny details, a simplified independent component correlation algorithm (ICA)-based local similarity stereo matching algorithm is proposed. In order to improve the DispNetC, the proposed algorithm first offers the simplified independent component correlation algorithm (SICA) cost aggregation. Then, the algorithm introduces the matching cost volume pyramid, which simplifies the pre-processing process for the ICA. Also, the SICA loss function is defined. Next, the region-wise loss function combined with the pixel-wise loss function is defined as a local similarity loss function to improve the spatial structure of the disparity map. Finally, the SICA loss function is combined with the local similarity loss function, which is defined to estimate the disparity map and to compensate the edge information of the disparity map. Experimental results on KITTI dataset show that the average absolute error of the proposed algorithm is about 37% lower than that of the DispNetC, and its runtime consuming is about 0.6 s lower than that of GC-Net. Numéro de notice : A2021-176 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s00371-020-01811-x date de publication en ligne : 15/02/2020 En ligne : https://doi.org/10.1007/s00371-020-01811-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97286 [article]

A general method for the classification of forest stands using species composition and vertical and horizontal structure / Miquel de Cáceres in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 2 (June 2019) Titre : A general method for the classification of forest stands using species composition and vertical and horizontal structure Type de document : Article/Communication Auteurs : Miquel de Cáceres, Auteur ; Santiago Martín-Alcón, Auteur ; José Ramon Gonzalez-Olabarria, Auteur ; Lluis Coll, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse bivariée [Termes descripteurs IGN] analyse univariée [Termes descripteurs IGN] Catalogne (Espagne) [Termes descripteurs IGN] composition floristique [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] similitude [Termes descripteurs IGN] structure d'un peuplement forestier [Termes descripteurs IGN] typologie forestière [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Context : Forest typologies are useful for many purposes, including forest mapping, assessing habitat quality, studying forest dynamics, or defining sustainable management strategies. Quantitative typologies meant for forestry applications normally focus on horizontal and vertical structure of forest plots as main classification criteria, with species composition often playing a secondary role. The selection of relevant variables is often idiosyncratic and influenced by a priori expectations of the forest types to be distinguished. Aims : We present a general framework to define forest typologies where the dissimilarity between forest stands is assessed using coefficients that integrate the information of species composition with the univariate distribution of tree diameters or heights or the bivariate distribution of tree diameters and heights. Methods : We illustrate our proposal with the classification of forest inventory plots in Catalonia (NE Spain), comparing the results obtained using the bivariate distribution of diameters and heights to those obtained using either tree heights or tree diameters only. Results : The number of subtypes obtained using the tree diameter distribution for the calculation of dissimilarity was often the same as those obtained from the tree height distribution or to those using the bivariate distribution. However, classifications obtained using the three approaches were often different in terms of forest plot membership. Conclusion : The proposed classification framework is particularly suited to define forest typologies from forest inventory data and allows taking advantage of the bivariate distribution of diameters and heights if both variables are measured. It can provide support to the development of typologies in situations where fine-scale variability of topographic, climatic, and legacy management factors leads to fine-scale variation in forest structure and composition, including uneven-aged and mixed stands. Numéro de notice : A2019-183 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0824-0 date de publication en ligne : 12/04/2019 En ligne : https://doi.org/10.1007/s13595-019-0824-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92704 [article]

Using interactions and dynamics for mining groups of moving objects from trajectory data / Corrado Loglisci in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 7-8 (July - August 2018) . - pp 1436 - 1468 Titre : Using interactions and dynamics for mining groups of moving objects from trajectory data Type de document : Article/Communication Auteurs : Corrado Loglisci, Auteur Année de publication : 2018 Article en page(s) : pp 1436 - 1468 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] objet mobile [Termes descripteurs IGN] similitude [Termes descripteurs IGN] trajectoire [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Advances in tracking technology enable the gathering of spatio-temporal data in the form of trajectories, which when analysed can convey useful knowledge. In particular, discovering groups of moving objects is a valuable means for a wide class of problems related to mobility. The task of group mining has been investigated by considering mostly the spatial closeness and similarity of the trajectories, while little attention has been paid to the relationships between the trajectories and time-changing nature of the trajectories. The relationships may provide evidence of interactions between the moving objects. The time-changing nature may provide evidence of dynamics of the movements. Therefore, interactions and dynamics can be sources of information to be considered in order to discover new forms of groups. Motivated by this, we introduce the concept of crews and propose a method to discover crews. A crew gathers moving objects with similar interactions and similar dynamics. The proposed method relies on i) new movement parameters, which explicitly consider interactions and dynamics, and ii) a distance-free clustering algorithm, which groups objects based on the similarity of the movement parameters. We conduct extensive experiments, which include a quantitative evaluation of the quality of the crews and comparison with alternative solutions. Numéro de notice : A2018-280 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2017.1416473 date de publication en ligne : 21/12/2017 En ligne : https://doi.org/10.1080/13658816.2017.1416473 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90362 [article]

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Graph-based matching of points-of-interest from collaborative geo-datasets / Tessio Novack in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 3 (March 2018) Titre : Graph-based matching of points-of-interest from collaborative geo-datasets Type de document : Article/Communication Auteurs : Tessio Novack, Auteur ; Robin Peters, Auteur ; Alexander Zipf, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes descripteurs IGN] appariement de points [Termes descripteurs IGN] conflation [Termes descripteurs IGN] Foursquare [Termes descripteurs IGN] Londres [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] similitude Résumé : (Auteur) Several geospatial studies and applications require comprehensive semantic information from points-of-interest (POIs). However, this information is frequently dispersed across different collaborative mapping platforms. Surprisingly, there is still a research gap on the conflation of POIs from this type of geo-dataset. In this paper, we focus on the matching aspect of POI data conflation by proposing two matching strategies based on a graph whose nodes represent POIs and edges represent matching possibilities. We demonstrate how the graph is used for (1) dynamically defining the weights of the different POI similarity measures we consider; (2) tackling the issue that POIs should be left unmatched when they do not have a corresponding POI on the other dataset and (3) detecting multiple POIs from the same place in the same dataset and jointly matching these to the corresponding POI(s) from the other dataset. The strategies we propose do not require the collection of training samples or extensive parameter tuning. They were statistically compared with a “naive”, though commonly applied, matching approach considering POIs collected from OpenStreetMap and Foursquare from the city of London (England). In our experiments, we sequentially included each of our methodological suggestions in the matching procedure and each of them led to an increase in the accuracy in comparison to the previous results. Our best matching result achieved an overall accuracy of 91%, which is more than 10% higher than the accuracy achieved by the baseline method. Numéro de notice : A2018-103 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030117 En ligne : https://doi.org/10.3390/ijgi7030117 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89518 [article]

Similarity measurement of metadata of geospatial data : an artificial neural network approach / Zugang Chen in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 3 (March 2018) Titre : Similarity measurement of metadata of geospatial data : an artificial neural network approach Type de document : Article/Communication Auteurs : Zugang Chen, Auteur ; Jia Song, Auteur ; Yaping Yang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] métadonnées [Termes descripteurs IGN] métadonnées géographiques [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] similitude Résumé : (Auteur) To help users discover the most relevant spatial datasets in the ever-growing global spatial data infrastructures (SDIs), a number of similarity measures of geospatial data based on metadata have been proposed. Researchers have assessed the similarity of geospatial data according to one or more characteristics of the geospatial data. They created different similarity algorithms for each of the selected characteristics and then combined these elementary similarities to the overall similarity of the geospatial data. The existing combination methods are mainly linear and may not be the most accurate. This paper reports our experiences in attempting to learn the optimal non-linear similarity integration functions, from the knowledge of experts, using an artificial neural network. First, a multiple-layer feed forward neural network (MLFFN) was created. Then, the intrinsic characteristics were used to represent the metadata of geospatial data and the similarity algorithms for each of the intrinsic characteristics were built. The training and evaluation data of MLFFN were derived from the knowledge of domain experts. Finally, the MLFFN was trained, evaluated, and compared with traditional linear combination methods, which was mainly a weighted sum. The results show that our method outperformed the existing methods in terms of precision. Moreover, we found that the combination of elementary similarities of experts to the overall similarity of geospatial data was not linear. Numéro de notice : A2018-094 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7030090 En ligne : https://doi.org/10.3390/ijgi7030090 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89506 [article]

Geometric quality assessment of trajectory-generated VGI road networks based on the symmetric arc similarity / Yan Lyu in Transactions in GIS, vol 21 n° 5 (October 2017)  

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A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships / Ick-Hoi Kim in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)  

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Cross-domain image localization by adaptive feature fusion / Neelanjan Bhowmik (2017)  

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Automatic registration of MLS point clouds and SfM meshes of urban area / Reiji Yoshimura in Geo-spatial Information Science, vol 19 n° 3 (October 2016)  

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Contributions à la segmentation non supervisée d'images hyperspectrales : trois approches algébriques et géométriques / Saadallah El Asmar (2016)  

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Probabilistic multi-person localisation and tracking / Tobias Klinger (2016) 

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Polygonal clustering analysis using multilevel graph-partition / Wanyi Wang in Transactions in GIS, vol 19 n° 5 (October 2015)  

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Integrating user needs on misclassification error sensitivity into image segmentation quality assessment / Hugo Costa in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)

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UK open source crime data: accuracy and possibilities for research / Lisa Tompson in Cartography and Geographic Information Science, Vol 42 n° 2 (April 2015)  

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Automatic registration of optical imagery with 3D LiDAR data using statistical similarity / Ebadat Ghanbari Parmehr in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)

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Improving representation of land-use maps derived from object-oriented image classification / Wenxiu Gao in Transactions in GIS, vol 17 n° 3 (June 2013)  

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Low altitude aerial photography applications for digital surface models creation in archaeology / José-Angel Martinez-Del-Pozo in Transactions in GIS, vol 17 n° 2 (April 2013)  

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Trajectories of moving objects on a network: detection of similarities, visualization of relations, and classification of trajectories / Yukio Sadahiro in Transactions in GIS, vol 17 n° 1 (February 2013)  

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Improved nonsubsampled contourlet transform for multi-sensor image registration / R. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 1 (January 2013)

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Sketch-Finder: efficient and effective sketch-based retrieval for large image collections / Carlos Alberto Pimentel Filho (August 2013)  

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Détection de changement 2D à partir d’imagerie satellitaire : Application à la mise à jour des bases de données géographiques / Nicolas Champion (2011)  

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Graph-based feature selection for object-oriented classification in VHR airborne imagery / T. Chen in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 2 (January 2011)  

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Similarity weighted instance-based learning for the generation of transition potentials in land use change modeling / F. Sangermano in Transactions in GIS, vol 14 n° 5 (October 2010)  

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Constrained free space diagrams: a tool for trajectory analysis / Kevin Buchin in International journal of geographical information science IJGIS, vol 24 n°7-8 (july 2010)  

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Segmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)  

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