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Geometric features and their relevance for 3D point cloud classification / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol IV-1/W1 (May 2017)
[article]
Titre : Geometric features and their relevance for 3D point cloud classification Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; Boris Jutzi, Auteur ; Clément Mallet , Auteur ; Michael Weinmann, Auteur Année de publication : 2017 Projets : 1-Pas de projet / Conférence : ISPRS 2017, Workshops HRIGI – CMRT – ISA – EuroCOW 06/06/2017 09/06/2017 Hanovre Allemagne ISPRS OA Annals Article en page(s) : pp 157 - 164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classe d'objets
[Termes IGN] classification
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage de données
[Termes IGN] étiquette de classe
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] interprétation automatique
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) In this paper, we focus on the automatic interpretation of 3D point cloud data in terms of associating a class label to each 3D point. While much effort has recently been spent on this research topic, little attention has been paid to the influencing factors that affect the quality of the derived classification results. For this reason, we investigate fundamental influencing factors making geometric features more or less relevant with respect to the classification task. We present a framework which consists of five components addressing point sampling, neighborhood recovery, feature extraction, classification and feature relevance assessment. To analyze the impact of the main influencing factors which are represented by the given point sampling and the selected neighborhood type, we present the results derived with different configurations of our framework for a commonly used benchmark dataset for which a reference labeling with respect to three structural classes (linear structures, planar structures and volumetric structures) as well as a reference labeling with respect to five semantic classes (Wire, Pole/Trunk, Façade, Ground and Vegetation) is available. Numéro de notice : A2017-860 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-IV-1-W1-157-2017 Date de publication en ligne : 30/05/2017 En ligne : https://doi.org/10.5194/isprs-annals-IV-1-W1-157-2017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89840
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol IV-1/W1 (May 2017) . - pp 157 - 164[article]The analysis and measurement of building patterns using texton co-occurrence matrices / Wenhao Yu in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)
[article]
Titre : The analysis and measurement of building patterns using texton co-occurrence matrices Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Tinghua Ai, Auteur ; Pengcheng Liu, Auteur ; Xiaoqiang Cheng, Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] données vectorielles
[Termes IGN] matrice de co-occurrence
[Termes IGN] métrique
[Termes IGN] modèle géométrique du bâti
[Termes IGN] reconnaissance de formes
[Termes IGN] reconstruction 2D du bâti
[Termes IGN] tessellation
[Termes IGN] triangulation de Delaunay
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) The representation and analysis of building patterns are critical for characterizing urban scenes and making decisions in urban planning. The evaluation of building patterns is a difficult spatial analysis problem that exhibits properties of symbolization, homogeneity and regularity. Open issues in this field include the development of approaches for representing building patterns and vector-based methods for computing various pattern metrics. In the image analysis domain, there are many methods for pattern recognition (e.g., texture analysis), but there are few corresponding solutions for vector data. The aim of this research is to develop several building pattern metrics and offer a texton co-occurrence matrix (TCM)-based method to quantitatively evaluate the features of building patterns. The procedure first constructs a spatial field based on a Delaunay triangulation skeleton to partition a set of buildings into a set of tessellation cells. The tessellations of building clusters have a similar structure as image representations, in that each cell corresponds to an image pixel. We then use the texton analysis to establish a matrix to describe the tessellation structure, including the neighboring relationships and individual attribute information. Finally, a set of feature descriptors is obtained from the TCM to capture the texture-related information of building groups. Through experiments on building pattern analysis and spatial queries, we show that the results of TCM-based evaluation of building patterns are consistent with those of human cognition. Numéro de notice : A2017-242 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1265121 En ligne : http://dx.doi.org/10.1080/13658816.2016.1265121 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85178
in International journal of geographical information science IJGIS > vol 31 n° 5-6 (May-June 2017)[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017031 RAB Revue Centre de documentation En réserve L003 Disponible A Topology-inferred graph-based heuristic algorithm for map simplification / QiuLei Guo in Transactions in GIS, vol 20 n° 5 (October 2016)
[article]
Titre : A Topology-inferred graph-based heuristic algorithm for map simplification Type de document : Article/Communication Auteurs : QiuLei Guo, Auteur ; Hassan A. Karimi, Auteur Année de publication : 2016 Article en page(s) : pp 775 – 789 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation
[Termes IGN] carte heuristique
[Termes IGN] graphe
[Termes IGN] méthode heuristique
[Termes IGN] polyligne
[Termes IGN] relation topologique
[Termes IGN] temps réel
[Termes IGN] voisinage (relation topologique)
[Vedettes matières IGN] GénéralisationRésumé : (auteur) In this article, we present a heuristic map simplification algorithm based on a novel topology-inferred graph model. Compared with the existing algorithms, which only focus either on geometry simplification or on topological consistency, our algorithm simplifies the map composed of series of polylines and constraint points while maintaining the topological relationships in the map, maximizing the number of removal points, and minimizing error distance efficiently. Unlike some traditional geometry simplification algorithms, such as Douglas and Peucker's, which add points incrementally, we remove points sequentially based on a priority determined by heuristic functions. In the first stage, we build a graph to model the topology of points in the map from which we determine whether a point is removable or not. As map generalization is needed in different applications with different requirements, we present two heuristic functions to determine the priority of points removal for two different purposes: to save storage space and to reduce computation time. The time complexity of our algorithm is math formula which is efficient enough to be considered for real-time applications. Experiments on real maps were conducted and the results indicate that our algorithm produces high quality results; one heuristic function results in higher removal points saving storage space and the other improves the time performance significantly. Numéro de notice : A2016-999 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12188 En ligne : http://dx.doi.org/10.1111/tgis.12188 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83779
in Transactions in GIS > vol 20 n° 5 (October 2016) . - pp 775 – 789[article]A novel methodology for identifying environmental exposures using GPS data / Andreea Cetateanu in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : A novel methodology for identifying environmental exposures using GPS data Type de document : Article/Communication Auteurs : Andreea Cetateanu, Auteur ; Bogdan-Alexandru Luca, Auteur ; Andrei Alin Popescu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1944 - 1960 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données GPS
[Termes IGN] durée de trajet
[Termes IGN] santé
[Termes IGN] véhicule automobile
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) Aim: While studies using global positioning systems (GPS) have the potential to refine measures of exposure to the neighbourhood environment in health research, one limitation is that they do not typically identify time spent undertaking journeys in motorised vehicles when contact with the environment is reduced. This paper presents and tests a novel methodology to explore the impact of this concern.
Methods: Using a case study of exposure assessment to food environments, an unsupervised computational algorithm is employed in order to infer two travel modes: motorised and non-motorised, on the basis of which trips were extracted. Additional criteria are imposed in order to improve robustness of the algorithm.
Results: After removing noise in the GPS data and motorised vehicle journeys, 82.43% of the initial GPS points remained. In addition, after comparing a sub-sample of trips classified visually of motorised, non-motorised and mixed mode trips with the algorithm classifications, it was found that there was an agreement of 88%. The measures of exposure to the food environment calculated before and after algorithm classification were strongly correlated.
Conclusion: Identifying non-motorised exposures to the food environment makes little difference to exposure estimates in urban children but might be important for adults or rural populations who spend more time in motorised vehicles.Numéro de notice : A2016-572 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1145682 En ligne : http://dx.doi.org/10.1080/13658816.2016.1145682 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81728
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1944 - 1960[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Change detection between SAR images using a pointwise approach and graph theory / Minh-Tan Pham in IEEE Transactions on geoscience and remote sensing, vol 54 n° 4 (April 2016)
[article]
Titre : Change detection between SAR images using a pointwise approach and graph theory Type de document : Article/Communication Auteurs : Minh-Tan Pham, Auteur ; Grégoire Mercier, Auteur ; Julien Michel, Auteur Année de publication : 2016 Article en page(s) : pp 2020 - 2032 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bruit rose
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] graphe
[Termes IGN] image radar
[Termes IGN] image radar moirée
[Termes IGN] relation topologique
[Termes IGN] traitement du signal
[Termes IGN] voisinage (relation topologique)Résumé : (Auteur) This paper investigates the problem of change detection in multitemporal synthetic aperture radar (SAR) images. Our motivation is to avoid using a large-size dense neighborhood around each pixel to measure its change level, which is usually considered by classical methods in order to perform their accurate detectors. Therefore, we propose to develop a pointwise approach to detect land-cover changes between two SAR images employing the principle of signal processing on graphs. First, a set of characteristic points is extracted from one of the two images to capture the image's significant contextual information. A weighted graph is then constructed to encode the interaction among these keypoints and hence capture the local geometric structure of this first image. With regard to this graph, the coherence of the information carried by the two images is considered for measuring changes between them. In other words, the change level will depend on how much the second image still conforms to the graph structure constructed from the first image. Additionally, due to the presence of speckle noise in SAR imaging, the log-ratio operator will be exploited to perform the image comparison measure. Experimental results performed on real SAR images show the effectiveness of the proposed algorithm, in terms of detection performance and computational complexity, compared to classical methods. Numéro de notice : A2016-838 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2493730 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2493730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82882
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 4 (April 2016) . - pp 2020 - 2032[article]µ-shapes: Delineating urban neighborhoods using volunteered geographic information / Matt Aadland in Journal of Spatial Information Science (JoSIS), n° 12 (March 2016)PermalinkA computational introduction to digital image processing / Alasdair McAndrew (2016)PermalinkPermalinkSemantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers / Martin Weinmann in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)PermalinkContextual classification of point cloud data by exploiting individual 3d neigbourhoods / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)PermalinkCharacterization of neighborhood sensitivity of an irregular cellular automata model of urban growth / Khila R. Dahal in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)PermalinkSpatial-aware dictionary learning for hyperspectral image classification / Ali Soltani-Farani in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkAnalyzing relatedness by toponym co-occurrences on web pages / Yu Liu in Transactions in GIS, vol 18 n° 1 (February 2014)PermalinkTowards 3D lidar point cloud registration improvement using optimal neighborhood knowledge / Adrien Gressin in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)PermalinkImproving 3D lidar point cloud registration using optimal neighborhood knowledge / Adrien Gressin in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)Permalink