title: Correspondence propagation with weak priors.
abstract: For the problem of image registration, the top few reliable correspondences are often relatively easy to obtain, while the overall matching accuracy may fall drastically as the desired correspondence number increases. In this paper, we present an efficient feature matching algorithm to employ sparse reliable correspondence priors for piloting the feature matching process. First, the feature geometric relationship within individual image is encoded as a spatial graph, and the pairwise feature similarity is expressed as a bipartite similarity graph between two feature sets; then the geometric neighborhood of the pairwise assignment is represented by a categorical product graph, along which the reliable correspondences are propagated; and finally a closed-form solution for feature matching is deduced by ensuring the feature geometric coherency as well as pairwise feature agreements. Furthermore, our algorithm is naturally applicable for incorporating manual correspondence priors for semi-supervised feature matching. Extensive experiments on both toy examples and real-world applications demonstrate the superiority of our algorithm over the state-of-the-art feature matching techniques.
authors.affiliation: Department of Computer Science, Yale University, New Haven, CT 06511, USA. huan.wang@yale.edu
authors.forename: Huan
authors.initials: H
authors.lastname: Wang
authors.forename: Shuicheng
authors.initials: S
authors.lastname: Yan
authors.forename: Jianzhuang
authors.initials: J
authors.lastname: Liu
authors.forename: Xiaoou
authors.initials: X
authors.lastname: Tang
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique