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GIScience integrated with computer vision for the examination of old engravings and drawings / Motti Zohar in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 9 (September 2021) . - pp 1703 - 1724 Titre : GIScience integrated with computer vision for the examination of old engravings and drawings Type de document : Article/Communication Auteurs : Motti Zohar, Auteur ; Ilan Shimshoni, Auteur Année de publication : 2021 Article en page(s) : pp 1703 - 1724 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] carte en 3D [Termes IGN] carte profonde [Termes IGN] dessin [Termes IGN] extraction de données [Termes IGN] Israël [Termes IGN] Jérusalem [Termes IGN] patrimoine culturel [Termes IGN] paysage [Termes IGN] Ransac (algorithme) [Termes IGN] système d'information géographique [Termes IGN] vision par ordinateur Résumé : (auteur) Landscape reconstructions and deep maps are two major approaches in cultural heritage studies. In general, they require the use of historical visual sources such as maps, graphic artworks, and photographs presenting areal scenes, from which one can extract spatial information. However, photographs, the most accurate and reliable source for scenery reconstruction, are available only from the second half of the 19th century onward. Thus, for earlier periods one can rely only on old artworks. Nevertheless, the accuracy and inclusiveness of old artworks are often questionable and must be verified carefully. In this paper, we use GIScience methods with computer-vision capabilities to interrogate old engravings and drawings as well as to develop a new approach for extracting spatial information from these scenic artworks. We have inspected four old depictions of Jerusalem and Tiberias (Israel) created between the 17th and 19th centuries. Using visibility analysis and a RANSAC algorithm we identified the locations of the artists when they drew the artworks and evaluated the accuracy of their final products. Finally, we re-projected 3D map digitized features onto the drawing canvases, thus embedding features not originally drawn. These were then identified, enabling potential extraction of the spatial information they may reflect. Numéro de notice : A2021-592 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1874957 Date de publication en ligne : 25/02/2021 En ligne : https://doi.org/10.1080/13658816.2021.1874957 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98213 [article]

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