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dc.contributor.authorSeidl, Markusen_US
dc.contributor.authorBreiteneder, Christianen_US
dc.contributor.editorFranco Niccolucci and Matteo Dellepiane and Sebastian Pena Serna and Holly Rushmeier and Luc Van Goolen_US
dc.date.accessioned2013-10-31T10:33:36Z
dc.date.available2013-10-31T10:33:36Z
dc.date.issued2011en_US
dc.identifier.isbn978-3-905673-86-9en_US
dc.identifier.urihttp://dx.doi.org/10.2312/PE/VAST/VAST11S/045-048en_US
dc.description.abstractWith the advances of digital photography, the number of high quality images of rock panels containing petroglyphs grows steadily. Different time-consuming manual methods to determine and document the exact shapes and spatial locations of petroglyphs on a panel have been carried out over decades. We aim at automated methods to a) segment rock images with petroglyphs, b) classify the petroglyphs and c) retrieve similar petroglyphs from different archives. In this short paper, we present an approach for the unsolved problem of rock art image segmentation. A first evaluation demonstrates promising results.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.4.6 [Image Processing and Computer Vision]: Segmentation-Pixel Classificationen_US
dc.titleDetection and Classification of Petroglyphs in Gigapixel Images -- Preliminary Resultsen_US
dc.description.seriesinformationVAST: International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage - Short and Project Papersen_US


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