A relevance feedback architecture for content-based multimedia information retrieval systems
Content-based multimedia information retrieval (MIR) has become one of the most active research areas in the past few years. Many retrieval approaches based on extracting and representing visual properties of multimedia data have been developed. While these approaches establish the viability of MIR based on visual features, techniques for incorporating human expertise directly during the query process to improve retrieval performance have not drawn enough attention. To address this limitation, this paper introduces a human-computer interaction based approach to MIR in which the user guides the system during retrieval using relevance feedback. Our experiments show that the retrieval performance improves significantly by incorporating humans in the retrieval process