48 - Beyond the Patterns - Robert Sablatnig (TU Vienna): Multispectral Imaging and Writer Identification for Historical Manuscripts/ClipID:48423 previous clip next clip

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Recording date 2023-05-31





Organisational Unit

Lehrstuhl für Informatik 5 (Mustererkennung)


Lehrstuhl für Informatik 5 (Mustererkennung)



We have the great honor to welcome Robert Sablatnig to our lab for an invited presentation!

Abstract:The Computer Vision Lab @ TU Wien is working on cultural heritage related fields for more than 20 years. This presentation gives an insight on the latest achievements in the area of multispectral imaging as a prerequisite for analyzing historic manuscripts and on Automatic Writer Identification (AWI) as one of the analysis fields in the area of historic documents. MultiSpectral Imaging (MSI) has become a popular tool to reveal properties and structures in cultural heritage objects that are hidden to the human observer. One of the inherent problems of MSI applications is chromatic aberration. Due to an extended spectral range, the effect appears more pronounced than in conventional photography in the visible spectrum. Our recent work is concerned with longitudinal chromatic aberrations, i.e. shifts of the focal plane along the principal axis of the camera, as they are hard to correct in post-processing and should be avoided during acquisition. To this end, a calibration scheme to measure the wavelength- and distance-dependent focal shift behavior of a given camera/lens system is proposed, which allows for a mechanical compensation at acquisition time.  The images taken are the basis for the subsequent AWI task, which 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. Therefore, current state-of-the-art methods in writer identification perform differently on historical documents.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.

Short Bio: Robert Sablatnig was born in KlagenfurtCarinthia, 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 Recognition 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 2018 founded Institute of Visual Computing & Human-Centered Technology, which he is heading since 2019. His research interests are 3D Computer Vision including Range Finder, Stereovision, Shape from X, Registration, Calibration, Robot Vision, Machine- and Deep Learning for Computer Vision, Video data analysis (Motion and Tracking), Automated Document Analysis, Multispectral Imaging, Virtual- and Augmented Reality, and Applications in Industry and Cultural Heritage Preservation. He edited 17 conference proceedings and is author or co-author of more than 300 referred scientific publications published in journals, at several international conferences and workshops. He served in many program committees for international conferences and as member of the editorial board and referee for international journals and conferences; is Vice President of the Austrian Association for Pattern Recognition (AAPR/OAGM), the Austrian branch of IAPR and the IEEE and legally sworn and certified expert witness for computer vision (allgemein beeideter und gerichtlich zertifizierter Sachverständiger).


Robert's Website: https://cvl.tuwien.ac.at/staff/robert-sablatnig/

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Music Reference: 
Damiano Baldoni - Thinking of You (Intro)
Damiano Baldoni - Poenia (Outro)

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