Bridging the Semantic Gap in Content Management Systems: Computational Media Aesthetics

With the explosion of online media and media-based services, a key challenge in the area of media management is automation of content annotation, indexing, and organization for efficient access, search, retrieval, and browsing applications. One of the major failings of current media annotation systems is the semantic gap which refers to the discontinuity between the simplicity of features or content descriptions that can be currently computed automatically and the richness of semantics in user queries posed for media search and retrieval. This paper proposes an approach that targets at bridging the semantic gap and building innovative content annotation and navigation services. The approach is founded upon an understanding of media elements and their role in synthesis and manipulation of program content with a systematic study of media productions. It proposes a framework for computational understanding of the dynamic nature of the narrative structure and techniques via analysis of the integration and sequencing of audio/visual elements. The resulting system will lead to automatic content organization and interpretation that provides high level and high quality content descriptions to aid in search, retrieval, and browsing and also to objective and consistent distillation of the common features of successful audio-visual strategies.