ixMan_Lab
2016-2022
iXMan_Lab is an acronym for interactive
Even though being situated in the Department of Informatics, the lab has been designed i) to be virtually placed within the Centre for Manuscript Studies (CSMC) as well as ii) to render web-based accessibility by e.g. scholars from selected pilot sub-projects of SFB 950 "Manuscript Cultures in Asia, Africa and Europe". In this vein, the interdisciplinary approach behind our lab facilitates both a joint requirement analysis in the context of design thinking and a
The lab provides an infrastructure, or even platform, for interdisciplinary teams by utilizing a multi-touch table environment with high-performance computing equipment as a medium for a two-fold aim: First, experimentally designing a manageable processing chain based on computational vision methods for analyzing digitized manuscripts and, second, freezing-in a validated (or even evaluated or benchmarked) processing chain by consensus in order to deliver a useful tool for a broad range of users. In terms of hardware capabilities, the laboratory currently has a custom-built 65" multi-touch table (MTT) supported by a multi-core gaming engine. Thus our laboratory is completely equipped for running GPU-accelerated image processing and analysis algorithms and, if necessary, running machine learning methods as well.
In recent years, the main focus of our iXMan_Lab has been set on the further development of the Advanced Manuscript Analysis Portal (AMAP) equipped with an intuitive, viz Visual Programming based, interaction paradigm in the context of a multi-touch table.
In general, our iXMan_Lab will allow interdisciplinary teams to intuitively customize various advanced image processing and analysis methods as processing chains through visual programming, touch-based interaction and joint experimentation with digital-born or digitized documents from a variety of application domains.
Former directors: H. Siegfried Stiehl, Prof. Dr.-Ing. & Vinodh Rajan Sampath, PhD
Technician: Dieter Jessen
PhD Members
Hussein Adnan Mohammed (until 2019)
Computational Analysis of Writing Style in Digitised Manuscripts
Dissertation, Department of Informatics
1st evaluator: H. S. Stiehl, 2nd evaluator: V. Maergner, 3rd evaluator: N. Vincent
Dissertation:
https://ediss.sub.uni-hamburg.de/volltexte/2019/9730/pdf/Dissertation.pdf
See also: Handwriting Analysis Tool v3.0 (HAT3)
https://www.fdr.uni-hamburg.de/record/902#.XptAd8gzaUk#.XptAd8gzaUk
as well as https://www.csmc.uni-hamburg.de/about/people/mohammed.html for recent work.
MS/BS Student Members
Master's Theses
Christopher Kassens (2020)
Gabor Wavelets based Detection and Description of Repetitive Line-like Textures in Digitized Documents: Theory and Experiments
1st supervisor: H. S. Stiehl, 2nd supervisor: V. R. Sampath
Parth Sarthi Pandey (2020)
An Interactive Experimental System for Computational Analysis of charaktêres Using Visual Programming (see also https://github.com/virtualvinodh/AMAP, PDF available soon)
1st supervisor: H. S. Stiehl, 2nd supervisor: V. R. Sampath
Tim Christopher Hahn (2019)
Computational Analysis of Characteres in Digitized Manuscripts: A Proof of Concept
1st supervisor: H. S. Stiehl, 2nd supervisor: Dr. Michael Kohs, Faculty of Humanities
Matthis Hauschild (2016)
Design and realization of a browser-based system for the analysis of digitized manuscripts
1st supervisor: H. S. Stiehl, 2nd supervisor: Dr. Benjamin Seppke
Bachelor's Theses
Dominik Hauser (2021)
Detektion gekrümmter linienartiger Texturen in digitalisierten Dokumenten mithilfe von Gabor-Filtern
1st supervisor: H. S. Stiehl, 2nd supervisor: C. Kassens
Marlon Kramer (2019)
Baseline Performance Characterization of SIFT and FAST using synthetic imagery
1st supervisor: H. S. Stiehl, 2nd supervisor: V. R. Sampath
Nico Noster (2019)
Visualizing SIFT and FAST based Workflow
1st supervisor: H. S. Stiehl, 2nd supervisor: V. R. Sampath
Publications
Hauser, D., Kassens, C. and Stiehl, H. S. (2022):
On Learning-free Detection and Representation of Textline Texture in Digitized Documents. In Proceedings of 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM), February 3-5, 2022, pp. 352-361 (ISBN 978-989-758-549-4, ISSN 2184-4313) (The full set of experiments in the paper can be seen here)
Parth Sarthi Pandey, Vinodh Rajan, H. Siegfried Stiehl, Michael Kohs:
Visual Programming-Based Interactive Analysis of Ancient Documents: The Case of Magical Signs in Jewish Manuscripts. ICPR Workshops (7) 2020: 156-170
Rajan Sampath, V., Stiehl, H.S. (2020):
Turning Black into White through Visual Programming: Peeking into the Black Box of Computational Manuscript Analysis. manuscript_cultures 15, pp. 61-72 (Proceedings of Third International Conference on Natural Sciences and Technology in Manuscript Analysis and Workshop OpenX for Interdisciplinary Computational Manuscript Research, Universität. Hamburg, Centre for the Study of Manuscript Cultures, June 12–14, 2018, Eds. O. Hahn, V. Märgner, I. Rabin, and H.S. Stiehl; available from https://www.csmc.uni-hamburg.de/publications/mc/mc15.html)
Vinodh Rajan Sampath, H. Siegfried Stiehl:
Making DIA Accessible to Non-Experts: Designing a Visual Programming Language for Document Image Analysis . In 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 23-27. (pdf)
Thomas Konidaris, Volker Märgner, Hussein Adnan Mohammed, H. Siegfried Stiehl:
Efficient Keypoint Reduction for Document Image Matching. In ICPRAM 2019: 664-670.
Vinodh Rajan Sampath, H. Siegfried Stiehl:
AMAP: A Visual Programming Language Based System to Support Document Image Analysis . In Proceedings of Mensch & Computer 2019, 881-884. (pdf)
Vinodh Rajan Sampath, H. Siegfried Stiehl:
Advanced Manuscript Analysis Portal (AMAP): An Interactive Visual Language Environment for Manuscript Studies, In Proceedings of Digital Humanities Conference 2019 (Annual International Conference of the Alliance of Digital Humanities Organizations)", July 9-12, 2019, Utrecht. (pdf)
Vinodh Rajan Sampath, H. S. Stiehl:
From Eye-to-Eye to Hand-in-Hand: Collaborative Solution Building in Interdisciplinary Manuscript Research ,
Vinodh Rajan Sampath, H. Siegfried Stiehl:
Bringing Paleography to the Table: Developing an Interactive Manuscript Exploration System for Large Multi-Touch Devices ,
Hussein Adnan Mohammed, Volker Märgner, H. Siegfried Stiehl:
Writer Identification for Historical Manuscripts: Analysis and Optimisation of a Classifier as an Easy-to-Use Tool for Scholars from the Humanities. ICFHR 2018: 534-539. (pdf)
Hussein Mohammed, Volker Märger, Thomas Konidaris, H. Siegfried Stiehl:
Normalised Local Naive Bayes Nearest-Neighbour Classifier for Offline Writer Identification. In Document Analysis and Recognition (ICDAR), 14th International Conference on. IEEE, 2017, Kyoto, Japan, pp. 1013-1018. (pdf)
See also: Hand Writing Analysis Tool