Master data

Title: An extensible framework for knowledge-based multimedia adaptation
Subtitle:
Abstract: Multimedia content is becoming increasingly important in many areas not only for pure entertainment but also for commercial or educational purposes like, e.g., distance learning or online training. In parallel, the rapid evolution in the hardware sector brought up various new (mobile) end user devices like pocket PCs or mobile phones that are capable of displaying such content. Due to the different capabilities and usage environments of these devices, the basic multimedia content has to be adapted in order to fit the specific devices' capabilities and requirements, whereby such transformations typically include changes in the display size or quality adaptation. Based on the capabilities of the target device that can be expressed using recent multimedia standards like MPEG-21, these adaptation steps are typically carried out by the video server or a proxy node before the data is transferred to the client. In this paper, we present a software framework and implementation of such a multimedia server add-on that advances state-of-the-art technology in two ways. First, the framework supports the integration of various (already existing) multimedia transformation tools based on declarative interface and semantic capability descriptions in a way comparable to Semantic Web Services approaches. Second, by using the components' capability descriptions and the usage environment of the end user device, we employ a knowledge-based planning approach for dynamically constructing and executing the needed transformation program for a specific multi-media content request.
Keywords:
Publication type: Article in compilation (Authorship)
Publication date: 05.2004 (Print)
Published by: Proceedings of the 17th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems
Proceedings of the 17th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems
to publication
 ( Springer Verlag; B. Orchard, Ch. Yang, A. Moonis )
Title of the series: LNCS
Volume number: -
First publication: Yes
Page: pp. 144 - 153

Versionen

Keine Version vorhanden
Publication date: 05.2004
ISBN:
  • 3-5402-2007-0
ISSN: -
Homepage: -

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

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Subject areas No subject area selected
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: n.a.)
working groups No working group selected

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