Using Context and Fuzzy Relations to Interpret Multimedia Content

Object detection techniques are coming closer to the automatic detection and identification of objects in multimedia documents. Still, this is not sufficient for the understanding of multimedia content, mainly because a simple object may be related to multiple topics, few of which are indeed related to a given document. In this paper we determine the thematic categories that are related to a document based on the objects that have been automatically detected in it. Our approach relies on stored knowledge and a fuzzy hierarchical clustering algorithm; this algorithm uses a similarity measure that is based on the notion of context. The context is extracted using fuzzy ontological relations.