Intelligent Content and Semantics
Annotation of multimedia by employing human-machine synergy that optimizes user effort
The need for annotated multimedia content is more pressing than ever before. The fully automated annotation has made recently large progress but faces limitations and unsolved issues. Thus, the machine-only annotation appears immature although presenting promising achievements. On the other hand, manual (human) annotation is very cost-prohibitive.
The CASAM project is focusing on facilitating the synergy of human and machine intelligence to significantly speed up the task of human-produced semantic annotation of multimedia content. The project is developing an annotation tool that will augment machine knowledge with human input with the target of minimizing user effort. The project research focus lies in the domains of Reasoning for Multimedia Interpretation (RMI), Knowledge-Driven Multimedia Analysis (KDMA) and Human-Computer Interaction (HCI).
The annotation tool will be able to function within the modelled domain of news production of News Agencies and Broadcasters. However, the methods that will be developed will not be bound to the chosen domain, but will be also applicable for the annotation of multimedia documents in a variety of contexts, ensuring generality of the system’s usage.
Field of science
- /humanities/arts/modern and contemporary art/radio and television
- /natural sciences/computer and information sciences/artificial intelligence/machine learning/deep learning
Call for proposal
See other projects for this call
Funding SchemeCP - Collaborative project (generic)
6211 XX Maastricht
1503 809 Lisboa