Study of Context Inuence on Classiers Trained under Dierent Video-Document Representations

The problem of content-based video retrieval continues to pose a challenge to the research community, the performance of video retrieval systems being low due to the semantic gap. In this paper we consider whether taking advantage of context can aid the video retrieval process by making the prediction of relevance easier, i.e. if it is easier for a classication system to predict the relevance of a video shot under a given context, then that context has potential in also improving retrieval, since the underlying features better dierentiate relevant from non-relevant video shots. We use an operational denition