A strategy based on non-extensive statistics to improve frame-matching algorithms under large viewpoint changes
作者：
Highlights：
• We present a method for Fiducial Point Description based on non-extensive physical systems.
• We test the proposed method under what we call severe conditions, little tested in the literature.
• We compare the proposed method with the main methods found in the literature, showing that the proposed method surpasses all others.
• We present a new methodology to measure the performance of the studied algorithms.
• We show that the database used represents non-extensive physical systems.
摘要
•We present a method for Fiducial Point Description based on non-extensive physical systems.•We test the proposed method under what we call severe conditions, little tested in the literature.•We compare the proposed method with the main methods found in the literature, showing that the proposed method surpasses all others.•We present a new methodology to measure the performance of the studied algorithms.•We show that the database used represents non-extensive physical systems.
论文关键词：SIFT,Tsallis statistics,q-Gaussian function,Image matching,Image registration
论文评审过程：Received 17 June 2018, Revised 2 February 2019, Accepted 13 March 2019, Available online 22 March 2019, Version of Record 1 April 2019.
论文官网地址：https://doi.org/10.1016/j.image.2019.03.007
