Robust feature matching using guided local outlier factor

作者：

Highlights：

• We propose a novel non-iterative approach for robust feature matching.

• Heavy outliers can be detected and removed by the guided local outlier factor.

• Multi-granularity neighborhood structure-preserving prevents the matching collapse.

摘要

•We propose a novel non-iterative approach for robust feature matching.•Heavy outliers can be detected and removed by the guided local outlier factor.•Multi-granularity neighborhood structure-preserving prevents the matching collapse.

论文关键词：Feature matching,Mismatch removal,Rejecting outliers,Locality preserving,Image matching

论文评审过程：Received 26 December 2019, Revised 18 January 2021, Accepted 5 April 2021, Available online 12 April 2021, Version of Record 23 April 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.107986