Content-based Image Retrieval with Multinomial Relevance Feedback
Dorota Glowacka (University College London) and John Shawe-Taylor (University College London);
JMLR W&P 13:111-125, 2010.
Abstract
The paper considers an interactive search paradigm in which at each
round a user is presented with a set of k images and is required to
select one that is closest to her target. Performance is measured by
the number of rounds needed to identify a specific target image or
to find an image among the t nearest neighbours to the target in the
database. Building on earlier work we assume a multinomial user
model with the probabilities of response proportional to a function of
the distance to the target. The conjugate prior Dirichlet distribution
is used to model the problem motivating an algorithm that trades
exploration and exploitation in presenting the images in each round.
Experimental results verify the fit of the model with the problem as
well as show that the new approach compares favourably with previous
work.
