Abstract
3D digital archiving of cultural heritage has been conducting actively all over the world. Although the applications using the obtained digital 3D scan data are widely developed, their data management and quality verification does not conducted properly. To overcome this problem, we propose a novel verification framework based on the comparisons of shape and color information between an original image and an image from 3D scan data (i.e., mesh data with color mapping). Firstly, to verify that they are the identical object, we use the shape contexts information based on a machine learning technique. Secondly, we compare the color information between them for verifying its quality of color mapping. Utilizing the proposed framework, we expect that non-experts can verify the quality of 3D scan data automatically, thus, museum itself will be able to manage the 3D scan data systematically and reliably.
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This research is supported by 2018 Support Project for Academic Research on Traditional Culture in Korea National University of Cultural Heritage.
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Oh, Je., Yu, J. (2018). Automatic Verification Framework of 3D Scan Data for Museum Collections. In: Ioannides, M., et al. Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2018. Lecture Notes in Computer Science(), vol 11197. Springer, Cham. https://doi.org/10.1007/978-3-030-01765-1_30
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