Relevance feedback for image retrieval in structured multi-feature spaces
Divna Djordjevic, Ebroul Izquierdo · 2006
An approach for content-based image retrieval with relevance feedback based on a structured multi-feature space is proposed. It uses a novel kernel for merging multiple feature subspaces into a complementary space. The kernel exploits nature of the data by assigning appropriate weights for each feature set. The weights are dynamically adapted to user preferences in a relevance feedback scenario.