1 Current address: Computer Science Department, University of California Berkeley, Berkeley, CA 94720 Abstract Multimedia content is a central component of ondemand training and education delivered over the World Wide Web. Supporting asynchronous collaboration around educational multimedia is a key requirement for making the online educational environment effective. A multimedia annotation syst...

Focussing on the CLARIAH pilot project MIMEHIST: Annotating EYE’s Jean Desmet Collection, this short article discusses how MIMEHIST took inspiration from previous decades’ multimedia and video annotation scholarship in film studies to conceptualise functionalities for studying Eye Filmmuseum’s Collection Media Suite. The first situated itself relation past current approaches scholarly editions ...

In this paper, a knowledge representation infrastructure for semantic multimedia content analysis and reasoning is presented. This is one of the major objectives of the aceMedia Integrated Project where ontologies are being extended and enriched to include low-level audiovisual features, descriptors and behavioural models in order to support automatic content annotation. More specifically, the ...

The definition of ontologies within the multimedia domain still remains a challenging task, due to the complexity of multimedia data and the related knowledge. In this paper, we present a novel framework (MOWIS) aiming at realizing a system for building Multimedia Ontologies from Web Information Sources that has been realized within the PRIN 2007-2009 project Cooperare and presented in previous...

Content-based video retrieval is emerging as an important part in the process of utilization of various multimedia documents. In this report we present a novel system for the automatic indexing and content-based retrieval of multimedia documents. We chose the domain of Formula 1 sport videos because the manual annotation of Formula 1 races is complicated and time consuming. Our system uses mult...

This chapter summarises the approach and main achievements of the research project BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction). BOEMIE introduced a new approach towards the automation of knowledge acquisition from multimedia content. In particular, it developed and demonstrated the notion of evolving multimedia ontologies, which is used for the extraction, f...

This dissertation aims at building and using knowledge-driven models in order to improve the accuracy of automatic image annotation. Currently, many image annotation approaches are based on the automatic association between low-level or mid-level visual features and semantic concepts using machine learning techniques. Nevertheless, the only use of machine learning seems to be insufficient to br...

University education requires students to be trained both at university and external internship centres. Because of Covid-19, the availability multimedia resources examples practical contexts has become vital. Multimedia annotation can help reflect on professional world, collaborating interacting with colleagues online. This study aims encourage collaborative thinking by using new video technol...