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{{Paper
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https://ceur-ws.org/Vol-2299/keynote.pdf
Keynote
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Keynote
Keynote: Writer Identification on Historical Manuscripts
Robert Sablatnig, TU Wien, AT
Abstract
In recent years, Automatic Writer Identification (AWI) has received a lot of attention in the document analysis
community. However, most research has been conducted on contemporary benchmark sets. These datasets
typically do not contain any noise or artefacts caused by the conversion methodology. This article analyses
how current state-of-the-art methods in writer identification perform on historical documents. In contrast to
contemporary documents, historical data often contain artefacts such as holes, rips, or water stains which make
reliable identification error-prone.
Biographie
Robert Sablatnig was born in Klagenfurt, Carinthia, Austria, in 1965. From
1992 to 2003 he was an assistant professor (Univ.Ass.), and from 2003 to 2010
an associate professor (ao Univ.Prof.) of computer vision at the Pattern Recog-
nition and Image Processing Group. From 2005 to 2017 he was the head of the
Institute of Computer Aided Automation. Since 2010 he is heading the Computer
Vision Lab, which is part of the newly founded Institute of Visual Computing &
Human-Centered Technology (TU Wien), engaged in research, project leading, and
teaching. His research interests are 3D Computer Vision including Range Finder,
Stereovision, Shape from X, Registration, Calibration, Robot Vision; Automatic
Visual Inspection, Hierarchical Pattern Recognition, Video data analysis (Motion
and Tracking), Automated Document Analysis, Multispectral Imaging, Virtual- and
Augmented Reality, and Applications in Industry and Cultural Heritage Preserva-
tion.
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