A content-based image retrieval system based on relevance feedback is proposed. The system relies on an interactive search paradigm where at each round a user is presented with k images and selects the one closest to her target. The approach based on hierarchical Gaussian Process bandits is used to trade exploration and exploitation in presenting the images in each round. Experimental results show that the new approach compares favorably with previous work.