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Extracting building patterns with multilevel graph partition and building grouping / Shihong Du in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 122 (December 2016) . - pp 81 – 96 Titre : Extracting building patterns with multilevel graph partition and building grouping Type de document : Article/Communication Auteurs : Shihong Du, Auteur ; Liqun Luo, Auteur ; Kai Cao, Auteur ; Mi Shu, Auteur Année de publication : 2016 Article en page(s) : pp 81 – 96 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] extraction automatique [Termes IGN] figure géométrique [Termes IGN] graphe [Termes IGN] partition des données [Termes IGN] paysage urbain [Termes IGN] reconstruction 2D du bâti Résumé : (Auteur) Building patterns are crucial for urban landscape evaluation, social analyses and multiscale spatial data automatic production. Although many studies have been conducted, there is still lack of satisfying results due to the incomplete typology of building patterns and the ineffective extraction methods. This study aims at providing a typology with four types of building patterns (e.g., collinear patterns, curvilinear patterns, parallel and perpendicular groups, and grid patterns) and presenting four integrated strategies for extracting these patterns effectively and efficiently. First, the multilevel graph partition method is utilized to generate globally optimal building clusters considering area, shape and visual distance similarities. In this step, the weights of similarity measurements are automatically estimated using Relief-F algorithm instead of manual selection, thus building clusters with high quality can be obtained. Second, based on the clusters produced in the first step, the extraction strategies group the buildings from each cluster into patterns according to the criteria of proximity, continuity and directionality. The proposed methods are tested using three datasets. The experimental results indicate that the proposed methods can produce satisfying results, and demonstrate that the F-Histogram model is better than the two widely used models (i.e., centroid model and the Voronoi graph) to represent relative directions for building patterns extraction. Numéro de notice : A2016--022 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.10.001 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.10.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83885 [article]

Representation and discovery of building patterns: a three-level relational approach / Shihong Du in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 5-6 (May - June 2016) . - pp 1161 - 1186 Titre : Representation and discovery of building patterns: a three-level relational approach Type de document : Article/Communication Auteurs : Shihong Du, Auteur ; Mi Shu, Auteur ; Chen-Chieh Feng, Auteur Année de publication : 2016 Article en page(s) : pp 1161 - 1186 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] contrainte relationnelle [Termes IGN] généralisation cartographique [Termes IGN] généralisation du bâti [Termes IGN] généralisation géométrique (de visualisation) [Termes IGN] modèle numérique du bâti [Termes IGN] relation sémantique [Termes IGN] relation spatiale [Vedettes matières IGN] Généralisation Résumé : (Auteur) Building patterns exhibited collectively by a group of buildings are fundamental to understanding urban forms, classifying urban scenes, analyzing urban landscapes, and generalizing maps. The existing studies have used geometric homogeneity or regularity to represent and discover limited patterns for map generalization, or used interval and rectangle algebra to represent relations between spatial objects. These approaches, however, cannot illustrate how patterns are produced by using syntax or grammar (i.e. relations between buildings) to link words (i.e. buildings) into sentences (i.e. building patterns), making it impossible to represent and discover building patterns with diverse structures. This study presents a relation-based approach to formalize and discover arbitrary building patterns at three abstract levels. At the bottom level, a relative and local frame of reference is defined, and 169 basic relations are derived to represent relative positions between buildings. At the middle level, the 169 relations, qualitative angle description, and qualitative size are combined to formalize important semantic relations between two buildings, which include collinear, perpendicular, and parallel relations. At the top level, the relations at the bottom and middle levels are used to formalize three types of building patterns, including collinear patterns, the structured patterns with acceptable names, and other patterns of interest. Algorithms implementing the three levels of relations are presented and applied to demonstrate the effectiveness of the proposed approach in discovering building patterns from databases and querying building patterns. The results indicate that the relational approach is generic to effectively represent and discover building patterns with arbitrary structures. In addition, it complements the existing geometric methods for recognizing building patterns, and the interval and rectangle algebra for representing building relations. Numéro de notice : A2016-298 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1108421 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2015.1108421 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80884 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2016032	RAB	Revue	Centre de documentation	En réserve L003	Disponible
079-2016031	RAB	Revue	Centre de documentation	En réserve L003	Disponible