title: Pareto-depth for multiple-query image retrieval.
abstract: Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.
authors.forename: Ko-Jen
authors.initials: KJ
authors.lastname: Hsiao
authors.forename: Jeff
authors.initials: J
authors.lastname: Calder
authors.forename: Alfred O
authors.initials: AO
authors.lastname: Hero