articleIEEE Transactions on Image ProcessingFeb 20, 2014GREEN OA

Robust Point Matching via Vector Field Consensus

JMJiayi MaJZJi ZhaoJTJinwen TianAYAlan YuilleZTZhuowen Tu

Huazhong University of Science and Technology · Carnegie Mellon University · +2 more institutions

PubMed
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Abstract

In this paper, we propose an efficient algorithm, called vector field consensus, for establishing robust point correspondences between two sets of points. Our algorithm starts by creating a set of putative correspondences which can contain a very large number of false correspondences, or outliers, in addition to a limited number of true correspondences (inliers). Next, we solve for correspondence by interpolating a vector field between the two point sets, which involves estimating a consensus of inlier points whose matching follows a nonparametric geometrical constraint. We formulate this a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables indicating whether matches in the…

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Topics
Keywords
  • Mathematics
  • Outlier
  • RANSAC
  • Point set registration
  • Reproducing kernel Hilbert space
  • Maximum a posteriori estimation
  • Nonparametric statistics
  • Pattern recognition (psychology)
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