Robust image matching via local graph structure consensus
作者：
Highlights：
• We propose a novel objective for mismatch removal problem.
• Our method solves for the inlier set based on local graph structure consensus.
• It has a closed-form solution with linearithmic time and linear space complexity.
• It performs well in terms of robustness and effectiveness in feature matching.
• It has the potential for promoting high-level vision tasks, like image registration.
摘要
•We propose a novel objective for mismatch removal problem.•Our method solves for the inlier set based on local graph structure consensus.•It has a closed-form solution with linearithmic time and linear space complexity.•It performs well in terms of robustness and effectiveness in feature matching.•It has the potential for promoting high-level vision tasks, like image registration.
论文关键词：Image matching,Feature matching,Mismatch removal,Outlier,Image registration
论文评审过程：Received 19 August 2021, Revised 25 November 2021, Accepted 11 February 2022, Available online 13 February 2022, Version of Record 17 February 2022.
论文官网地址：https://doi.org/10.1016/j.patcog.2022.108588
