By Marios C. Angelides, Phivos Mylonas, Manolis Wallace
The emergence of content material- and context-aware se's, which not just customize looking and supply but additionally the content material, has brought on the emergence of recent infrastructures in a position to end-to-end ubiquitous transmission of customized multimedia content material to any gadget on any community at any time. Personalizing and adapting content material calls for processing of content material and spotting styles in clients’ behaviour at the different. Personalizing and adapting the semantic content material of multimedia permits purposes to make just-in-time clever judgements concerning this content material, which in flip makes interplay with the multimedia content material someone and separately profitable event. Highlighting the altering nature of the sector, Advances in Semantic Media model and Personalization, quantity discusses the cutting-edge, contemporary advances, and destiny outlooks for semantic media variation and personalization. themes contain: Collaborative content material Modeling automated content material characteristic Extraction to content material types Semantic Languages for content material Description Video content material edition Adaptive Video content material Retrieval content material Similarity Detection customized content material Podcasting Adaptive net interplay As content material and repair companies realize the price of recent prone and new markets, they're going to put money into applied sciences that adapt and customize content material. undefined, in reaction, has published new criteria equivalent to MPEG-7, MPEG21, and VC-1 that permit propagation of semantic media, variation, and personalization. for that reason, a vast diversity of purposes are rising throughout many sectors, resembling track, movie, video games, tv, and activities. Bringing jointly perception from researchers and practitioners, this booklet offers a sampling of the most recent pondering within the box.
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Additional resources for Advances in Semantic Media Adaptation and Personalization, Volume 2
For example, when a user senses many active users within a community, her behavior toward t hat community changes: she may spend more time a nd energy contributing to t he c ommunity b ecause sh e b elieves it to b e wo rthwhile, o r sh e may feel overwhelmed and be less likely to contribute. Consequently, this challenge bears strong relationships with the challenges of identity and emotional awareness discussed in the previous sections. Diﬀerent types of communities have attempted to cope with this challenge, most prominently online learning communities consisting of students and teachers, where a s ense of presence is vital to t he teaching and learning process.
The various segment decomposition tools such as the VideoSegmentTemporalDecomposition DS, the StillRegionSpatialDecomposition DS, a nd t he MovingRegionSpatioTemporalDecomposition DS en able t he media stream to be precisely decomposed in time and space. In this way, it is possible to reﬂect the temporal start and end points of content features, such as events, or the bounding areas of onscreen content features, such as objects. However, as is typical of XML-based representations, modiﬁcations may be made to the MPEG-7 metadata eﬃciently without causing disruption to other elements.
Separate MPEG-7 descriptions can be created on a per-user, per-stream basis and then aggregated with the creation and production description tools used to describe the creation and production of the multimedia content, including title, creator, classiﬁcation, purpose of the creation, and so forth. In particular, the Creation DS contains description tools for author-generated information about the creation process, including places, dates, actions, materials, staﬀ, and organizations involved. Revisions could feasibly be described as MPEG-7 descriptions by exploiting the standard’s ability to reference full and part descriptions in combination with the use of semantic description tools to refer to the revisions, such as the Event DS to describe the actions taken and the AgentObject DS to describe users, thereby facilitating identity awareness and enabling patterns and proﬁles to be developed.