Visual information retrieval using synthesized imagery

In this project (VIRSI) we investigate the promising contentbased retrieval paradigm known as interactive search or relevance feedback, and aim to extend it through the use of synthetic imagery. In relevance feedback methods, the user himself is a key factor in the search process as he provides positive and negative feedback on the results, which the system uses to iteratively improve the set of candidate results. In our approach we closely integrate the generation of synthetic imagery in the relevance feedback process through a new fundamental paradigm: Artificial Imagination (AIm). Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval – Query formulation, Relevance feedback, Search process. General Terms Algorithms, Human Factors. Keywords Content-based retrieval, principal component analysis, artificial imagination

• Type: Conference
• Year: 2007
• Where: CIVR
• Authors: Bart Thomee, Mark J. Huiskes, Erwin M. Bakker, Michael S. Lew
• Keywords: CIVR 2007, Relevance Feedback, Relevance Feedback Process, Synthetic Imagery