Abstract
A content-based image retrieval system based on multinomial 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 their ideal target. Two approaches, one based on the Dirichlet distribution and one based the Beta distribution, are used to model the problem motivating an algorithm that trades exploration and exploitation in presenting the images in each round. Experimental results show that the new approach compares favourably with previous work.
Authors
Dorota Glowacka, Yee Whye Teh, John Shawe-Taylor
Year
2016
Journal
arXiv preprint arXiv:1603.09522.
Keywords
Complex issues, Complex networks, and Complex Systems