So far, localization and description of these patterns is currently limited to micro-studies due to the involved extremely high manual annotation effort.
We therefore pursue two main objectives: 1) creation of a standardized annotation vocabulary to be applied for semantic annotations and 2) semi-automatic classification of audio-visual patterns by training models on manually assembled ground truth annotation data. The annotation vocabulary for empirical film studies and semantic annotations of audio-visual material based on Linked Open Data principles enables the publication, reuse, retrieval, and visualization of results from film-analytical methods. Furthermore, automatic analysis of video streams allows to speed up the process of extracting audio-visual patterns.
This paper will focus on describing the semantic data management of the project and the developed vocabulary for fine-grained semantic video annotation. Furthermore, we will give a short outlook on how we aim to integrate machine learning into the process of automatically detecting audio-visual patterns.
Senior Researcher
FIZ Karlsruhe – Leibniz Institute for Information Infrastructure
https://www.fiz-karlsruhe.de/
Harald Sack is Professor of Information Service Engineering at FIZ Karlsruhe, Leibniz Institute for Information Infrastructure and Karlsruhe Institute of Technology (KIT). After graduating in computer science at the University of the Federal Forces Munich, he worked as network engineer and project manager in the signal intelligence corps of the German Air Force.
Research Associate
Hasso Plattner Institute for IT-Systems Engineering
http://hpi.de/
Henning Agt-Rickauer is a research associate at the Hasso Plattner Institute for IT Systems Engineering in Potsdam, Germany. After studying Applied Computer Science at HTW Berlin (1998-2003), he was a research associate at Fraunhofer ISST (2003-2008) in the field of model-based software development.
