Multimedia Search with Pseudo-Relevance Feedback
journal contributionposted on 01.01.1997 by Rong Yan, Alexander Hauptmann, Rong Jin
Any type of content formally published in an academic journal, usually following a peer-review process.
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in both text and image modalities. While the normalization and combination of evidence is novel, this paper emphasizes the successful use of negative pseudo-relevance feedback to improve image retrieval performance. While the results are still far from perfect, pseudo-relevance feedback shows great promise for multimedia retrieval in very noisy data.