Fast Adaptation Decision Taking for Cross-Modal Multimedia Content Adaptation

Abstract

In order to enable transparent and convenient use of multimedia content across a wide range of networks and devices, content adaptation is an important issue within multimedia frameworks. The so called Digital Item Adaptation (DIA) standard is one of the core concepts of the MPEG-21 framework that will support the adaptation of multimedia resources according to device capabilities, underlying network characteristics, and user preferences. Most multimedia adaptation engines for providing Universal Multimedia Access (UMA) scale the content with respect to terminal capabilities and resource constraints. This paper focuses on the cross-modal adaptation decision taking process considering the user environment and terminal capabilities as well as resource limitations on the server, network, and client side. This approach represents a step toward increased Universal Multimedia Experience (UME). Based on four different algorithms for solving this optimization process, we present an evaluation of results gained by running their implementations on different test networks.

Intelligent multimedia engines for multimedia content adaptation

“…Mukherjee et al (2005) propose an optimisation-based model for terminal and network quality of service. Prangl et al (2006) propose another model for cross-modal multimedia content adaptation. They introduce target functions and solving algorithms, respectively.…”

A novel model of adaptation decision-taking engine in multimedia adaptation

“…Therefore, it cannot deal with dynamic user preferences. Mukherjee et al (2005) put forward an optimization-based model for terminal and network quality of service and Prangl et al (2006) propose another one for cross-modal multimedia content adaptation. They introduce target functions and solving algorithms, respectively.…”

A Framework for Personalized Utility-Aware IP-Based Multimedia Consumption

“…In order to achieve this target, a hybrid recommender system [2] is invoked to configure our cross-modal utility model [1]. Based on the individually configured utility model, the ADTE is calculating the optimum adaptation parameters based on optimization algorithms presented in [4]. The calculation requires additional information about the properties of the original content stream including the genre information.…”

“…This information is extracted/defined by the upload process into the user's content repository. In case of a live TV stream, the genre information is taken form the online program guide called hoerzu 4 . Finally, the ADTE generates an individual URL on which the client's player (or plug-in) can access the adapted content.…”