Content-Based Video Retrieval (CBVR) is a research area that has drawn a good deal of attention in recent years. The ability to retrieve videos similar to a given one in terms of implicit features (mainly pictorial features) and/or explicit characteristics (eg. semantic context) are the cornerstones of this growing interest. In this paper we present the results obtained within the project
, a CBVR system based on local color and motion signatures, our own video representation and different metrics of similarity among videos. The results for real videos point to promising advances, not only as regards the effectiveness of the system, but also in terms of its efficiency.