Point set registration with mixture framework and variational inference
作者：
Highlights：
• We define a Gaussian variational mixture model.
• We develop a three-phase registration strategy.
• We use anisotropic Gaussian components to weaken the effect of outliers.
• We apply the Dirichlet distribution to distinguish the missing points.
• The performance of our method outperforms state-of-art methods in this area.
摘要
•We define a Gaussian variational mixture model.•We develop a three-phase registration strategy.•We use anisotropic Gaussian components to weaken the effect of outliers.•We apply the Dirichlet distribution to distinguish the missing points.•The performance of our method outperforms state-of-art methods in this area.
论文关键词：Point set registration,Image registration,Gaussian variational mixture model,Variational inference
论文评审过程：Received 10 April 2019, Revised 29 November 2019, Accepted 25 March 2020, Available online 29 March 2020, Version of Record 10 April 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107345
