Integrating semantic analysis and scalable video coding for efficient content-based adaptation

Abstract

Scalable video coding has become a key technology to deploy systems where the adaptation of content to diverse constrained usage environments (such as PDAs, mobile phones and networks) is carried out in a simple and efficient way. Content-based adaptation and summarization are fields that aim for providing improved adaptation to the user, trying to optimize the semantic coverage in the adapted/summarized version. This paper proposes the integration of content analysis with scalable video adaptation paradigm. They must be fitted in such a way that the efficiency of scalable adaptation is not damaged. An integrated framework is proposed for semantic video adaptation, as well as an adaptive skimming scheme that can use the results of semantic analysis. They are described using the MPEG-21 DIA tools to provide the adaptation in a standard framework. Particularly, the case of activity analysis is described to illustrate the integration of semantic analysis in the framework, and its use for online content summarization and adaptation. Overall efficiency is achieved by means of computing activity using compressed domain analysis with several metrics evaluated as measures of activity.