Introduction - If you have any usage issues, please Google them yourself
We review recent advances in image retri . The two fundamental
components of a retri system, representation and learning,
are analyzed. Each component is decomposed into its constituent
building blocks: features, feature representation, and similarity
function for the representation short- and long-term procedures
for learning. We identify a series of requirements for each of the
sub-areas, e.g. optimality, invariance, perceptual relevance, computational
tractability, and point out various approaches proposed
to satisfy them. Several open problems are also identified