Video and Image Analytics
Digital tools for the analysis and annotation of films / videos, be they feature films, documentaries and experimental films as well as observational and eye-tracking videos, as well as extensive image datasets open up completely new possibilities in teaching and research. For a long time now, they also have been used outside traditional visual studies such as art history and film studies. The knowledge of digital tools and their underlying methods as well as the corresponding competence in using these tools is therefore of great importance. The module focuses on the application of the video analysis software VIAN as well as on the interpretation of the evaluation and visualization methods it provides.
- Visual Analytics and Deep Learning: interactive visualization and visualization guidelines
- Diagrammatics: epistemology of film visualizations
- Introduction and overview of the video annotation and visualization software VIAN
- VIAN-Coaching (in small groups)
Please note that the VIAN coaching is held in smaller groups. Depending on the number of applications, additional appointments may need to be made.
If necessary, you will receive support for installing VIAN.
At least Windows 8, macOS High Sierra or Linux Ubuntu 16.04 with at least 5 GB disc storage, and 8 GB RAM.
Recommended prerequisites: 16 GB RAM.
Please note that the required disk space also depends on the number and type of movies to be analyzed.
If VIAN is installed manually (and not with the installer), additional software is needed: Python3 and VLC 64-bit version.
Lecturers from the University of Zurich and the Zurich University of the Arts.
Language of Instruction
Drucker, Johanna (2016): “Graphical Approaches to the Digital Humanities”. In: Susan Schreibman, Ray Siemens und John Unsworth (Hg.): A New Companion to Digital Humanities. West Sussex: Wiley & Sons, Blackwell, S. 238‒250.
Execution of the Course
Duration: 3 days / 9 hours
Number of participants: Max. 24 or 5 for coaching sessions.
Place: Via Zoom, online.
Date/Time: Saturday, November 19, 2021; Saturday, November 26, 2021; Saturday, December 3, 2021.