MAC-REALM: A Video Content Feature Extraction and Modelling Framework

This paper discusses MAC-REALM, a framework for extraction of syntactic and semantic content features and content modelling with either little or no user interaction. The framework integrates a four filter-plane strategy: a pre-processing plane that filters redundant data, a syntactic feature extraction plane that filters syntactic features, a semantic relationships analysis and linkage plane that filters the spatial and temporal relationships of content features, and finally a content modelling plane where the syntactic and semantic content features are integrated into a content model. Each of the four planes is split into three layers: the content layer, where the content to be processed is stored; the application layer, where the content is converted into content descriptions; and the MPEG-7 layer, where content descriptions are serialized. Using MPEG-7 standards to produce the content model will provide wide-ranging interoperability while facilitating granular multi-content-type searches. MAC-REALM aims at ‘bridging’ the semantic gap, by integrating the syntactic and semantic content features from extraction through to modelling.