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  4. Ähnlichkeitsanalyse von Kunstwerken

Ähnlichkeitsanalyse von Kunstwerken

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  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users
  • An AI-based framework for visualizing and analyzing massive amounts of 4D tomography data for beamline end users

Ähnlichkeitsanalyse von Kunstwerken

Similarity learning for art analysis

(Third Party Funds Group – Sub project)

Overall project: Critical Catalogue of Luther Portraits (1519-1530)
Project leader: Andreas Maier
Project members: Andreas Maier, Vincent Christlein, Aline Sindel
Start date: June 1, 2018
End date: February 28, 2021
Acronym:
Funding source: andere Förderorganisation
URL: https://www.gnm.de/forschung/forschungsprojekte/luther-bildnisse/

Abstract

The analysis of the similarity of portraits is an important issue for many sciences such as art history or digital humanities, as for instance it might give hints concerning serial production processes, authenticity or temporal and contextual classification of the artworks.
In the project, first algorithms will be developed for cross-genre and multi-modal registration of portraits to overlay digitized paintings and prints as well as paintings acquired with different imaging systems such as visual light photography and infrared reflectography. Then, methods will be developed to objectively analyze the portraits according to their similarity.
This project is part of a joint project of the FAU, the Germanisches Nationalmuseum (GNM) in Nuremberg and the Technology Arts Sciences (TH Köln) in Cologne. Goal of the interdisciplinary project covering art history, art technology, reformation history and computer science is the creation of a critical catalogue of Luther portraits (1519-1530).

Publications

  • Sindel A., Maier A., Christlein V.:
    Art2Contour: Salient Contour Detection in Artworks Using Generative Adversarial Networks
    2020 IEEE International Conference on Image Processing (ICIP 2020) (Online (Abu Dhabi, United Arab Emirates), October 25, 2020 - October 28, 2020)
    DOI: 10.1109/ICIP40778.2020.9191117
    URL: https://www.researchgate.net/publication/346488040_Art2Contour_Salient_Contour_Detection_in_Artworks_Using_Generative_Adversarial_Networks
    BibTeX: Download
  • Sindel A., Maier A., Christlein V.:
    A Visualization Tool for Image Fusion of Artworks
    25th International Conference on Cultural Heritage and New Technologies (Online (Vienna, Austria), November 4, 2020 - November 6, 2020)
    URL: https://archiv.chnt.at/wp-content/uploads/A-Visualization-Tool-for-Image-Fusion-of-Artworks.pdf
    BibTeX: Download
  • Biendl M., Sindel A., Klinke T., Maier A., Christlein V.:
    Automatic Chain Line Segmentation in Historical Prints
    International Workshop on Fine Art Pattern Extraction and Recognition (FAPER) at International Conference on Pattern Recognition (ICPR) (Online (Milan, Italy), January 11, 2021 - January 11, 2021)
    In: Pattern Recognition. ICPR International Workshops and Challenges 2021
    DOI: 10.1007/978-3-030-68796-0_47
    BibTeX: Download
  • Sindel A., Klinke T., Maier A., Christlein V.:
    ChainLineNet: Deep-Learning-Based Segmentation and Parameterization of Chain Lines in Historical Prints
    In: Journal of Imaging 7 (2021), Article No.: 120
    ISSN: 2313-433X
    DOI: 10.3390/jimaging7070120
    URL: https://www.mdpi.com/2313-433X/7/7/120
    BibTeX: Download
  • Sindel A., Maier A., Christlein V.:
    CraquelureNet: Matching The Crack Structure In Historical Paintings For Multi-Modal Image Registration
    2021 IEEE International Conference on Image Processing (ICIP) (Online ( Anchorage, AK, USA ), September 19, 2021 - September 22, 2021)
    DOI: 10.1109/ICIP42928.2021.9506071
    URL: https://www.researchgate.net/publication/354690882_CraquelureNet_Matching_The_Crack_Structure_In_Historical_Paintings_For_Multi-Modal_Image_Registration
    BibTeX: Download

Friedrich-Alexander-Universität Erlangen-Nürnberg
Lehrstuhl für Mustererkennung (Informatik 5)

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