2008 Second International Conference on Future Generation Communication and Networking Universal Video Adaptation Model for Contents Delivery Using Focus-of-Choice Model December 13-December 15 ISBN: 978-0-7695-3431-2
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FGCN.2008.206
Personalized video adaptation is expected to satisfy individual users' needs on video content. Multimedia data mining plays a significant role of video annotation to meet users' preference on video content. In this paper, a comprehensive solution for personalized video adaptation is proposed based on video content mining. Video content mining targets both cognitive content and affective content. Sometimes, users might prefer "emotional decision" to select their interested video content. The situation encourages the need for the personalized contents to provide the user in the best possible experience. We address the problem of video personalization. For the personalized content, we suggest the UVA (Universal-Video Adaptation) model that uses the video content description in MPEG-7 standard and MPEG-21 multimedia framework.
Index Terms:
Video Adaptation, Contents Delivery, Mpeg 21, UVA, Universal Video Adaptation
Citation:
Svetlana Kim, Yongik Yoon, "Universal Video Adaptation Model for Contents Delivery Using Focus-of-Choice Model," fgcn, vol. 1, pp.46-49, 2008 Second International Conference on Future Generation Communication and Networking, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||