Histogram of Oriented Gradients for Maya Glyph Retrieval

Simple item page
dc.contributor.authorFeldmann, Felixen_US
dc.contributor.authorBogacz, Bartoszen_US
dc.contributor.authorPrager, Christianen_US
dc.contributor.authorMara, Huberten_US
dc.contributor.editorTobias Schreck and Tim Weyrich and Robert Sablatnig and Benjamin Stularen_US
dc.date.accessioned2017-09-27T06:39:34Z
dc.date.available2017-09-27T06:39:34Z
dc.date.issued2017
dc.description.abstractDeciphering the Maya writing is an ongoing effort that has already started in the early 19th century. Inexpertly-created drawings of Maya writing systems resulted in a large number of misinterpretations concerning the contents of these glyphs. As a consequence, the decryption of Maya writing systems has experienced several setbacks. Modern research in the domain of cultural heritage requires a maximum amount of precision in capturing and analyzing artifacts so that scholars can work on - preferably - unmodified data as much as possible. This work presents an approach to Maya glyph retrieval based on a machine learning pipeline. A Support Vector Machine (SVM) classifier is trained based on the Histogram of Oriented Gradients (HOG) feature descriptors of the query glyph and random background image patches. Then a sliding window classifies regions into viable candidates on the scale pyramid of the document image to achieve scale invariance. The algorithm is demonstrated on two different data sets. First, photographs from a hand written codex and second 3D scans from stone engraved monuments. A large amount of future extensions lies ahead, comprising the extension to 3D, but also more sophisticated classification algorithms.en_US
dc.description.sectionheadersRetrieval, Classification, and Matching
dc.description.seriesinformationEurographics Workshop on Graphics and Cultural Heritage
dc.identifier.doi10.2312/gch.20171301
dc.identifier.isbn978-3-03868-037-6
dc.identifier.issn2312-6124
dc.identifier.pages115-118
dc.identifier.urihttps://doi.org/10.2312/gch.20171301
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/gch20171301
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectShape representations
dc.subjectObject identification
dc.subjectApplied computing
dc.subjectGraphics recognition and interpretation
dc.subjectOptical character recognition
dc.titleHistogram of Oriented Gradients for Maya Glyph Retrievalen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
115-118.pdf
Size:
1.93 MB
Format:
Adobe Portable Document Format
Download
Collections
GCH 2017 - Eurographics Workshop on Graphics and Cultural Heritage