Visual History of the Holocaust

Project Details


EU H2020

Grant Number





Robert Sablatnig


Martin Kampel
Daniel Helm


Rethinking Curation in the Digital Age

The Holocaust has been a central reference point for European history and a ‘negative founding myth’ of European integration. Nowadays, digital technologies and the Internet have profoundly transformed the concepts of history and visual evidence. Thus, the question of its representation becomes more relevant.

A consortium consisting of different international research institutions, museums, memorial sites and technology developers will together develop models and applications to respond to this challenge. The EU-funded Horizon 2020 project is coordinated by the Ludwig Boltzmann Institute for Digital History (Vienna) and the Austrian Film Museum (Vienna).

The main objectives of Visual History of the Holocaust are to find strategies and models which are able to understand and annotate the content of historical footage, images and other historical sources automatically. Furthermore, developed strategies and models will allow to dynamically find interrelations between film images with photographs and other sources like text-based documents, oral histories of contemporary witnesses as well as with images from subsequent filmic representations of the Holocaust.

The visual representation of the Holocaust has been an argumentative issue for artists, historians, educators and curators for decades. In an age of many possibilities to alter and manipulate digital images, questions of authenticity and appropriate use of technology become even more relevant. While Visual History of the Holocaust deals with specific films and historical events, it raises more general questions on what ‘digital curation’ entails.

For that reason, the project will make groundbreaking use of emerging technologies, including advanced digitization, automated analysis of images and text, time-based annotation and location-based services. The aim of the project is to generate new contexts of meaning to be explored in history, film and media studies, cultural studies and computer science. Based on this technology-enabled research new efficiency possibilities to represent and to interact with the Holocaust will be given to memorials, educational institutions and museums.

Project Consortium and Partners:
  • Ludwig Boltzmann Institute for Digital History (AT),  Coordinator
  • Austrian Film Museum (AT), Co-Coordinator
  • TU Wien (AT)
  • max.recall information systems Gmbh (AT)
  • Mauthausen Memorial (AT)
  • Center for Russian, Central European and Caucasian Studies (Centre National de la Recherche Scientifique) (FR)
  • The Hebrew University of Jerusalem (IL)
  • Deutsches Filminstitut & Filmmuseum (DE)
  • Justus Liebig University Giessen (DE)
  • Stiftung Bayerische Gedenkstätten – Dachau Concentration Camp Memorial Site (DE)
  • Stiftung niedersächsische Gedenkstätten – Bergen-Belsen Memorial (DE)
  • University of Bremen (DE)
  • National Archives and Records Administration (USA)
  • United States Holocaust Memorial Museum (USA)
  • Fritz Bauer Institut (DE)



  • Helm D., Kampel M. (2019) Shot Boundary Detection for Automatic Video Analysis of Historical Films. In: Cristani M., Prati A., Lanz O., Messelodi S., Sebe N. (eds) New Trends in Image Analysis and Processing – ICIAP 2019. ICIAP 2019. Lecture Notes in Computer Science, vol 11808. Springer, Cham
  • Daniel Helm and Martin Kampel. Video Shot Analysis for Digital Curation and Preservation of Historical Films. In Selma Rizvic and Karina Rodriguez Echavarria, editors, Eurographics Workshop on Graphics and Cultural Heritage. The Eurographics Association, 2019. ISBN 978-3-03868-082-6. doi: 10.2312/gch.20191344.
  • Helm D., Pointner B., Kampel M., Frame Border Detection for Digitized Historical Footage. Proceedings of the Joint Austrian Computer Vision and Robotics Workshop 2020, pp. 114-115, Graz, Austria, August 2020.
  • Helm D., Kampel M. (2020) Overscan Detection in Digitized Analog Films by Precise Sprocket Hole Segmentation. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science, Springer, Cham.