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Boosting Feature Matching Accuracy With Pairwise Affine Estimation.

Authors :
Dai, Ji
Jin, Shiwei
Zhang, Junkang
Nguyen, Truong Q.
Source :
IEEE Transactions on Image Processing. 2020, Vol. 29, p8278-8291. 14p.
Publication Year :
2020

Abstract

Local image feature matching lies in the heart of many computer vision applications. Achieving high matching accuracy is challenging when significant geometric difference exists between the source and target images. The traditional matching pipeline addresses the geometric difference by introducing the concept of support region. Around each feature point, the support region defines a neighboring area characterized by estimated attributes like scale, orientation, affine shape, etc. To correctly assign support region is not an easy job, especially when each feature is processed individually. In this article, we propose to estimate the relative affine transformation for every pair of to-be-compared features. This “tailored” measurement of geometric difference is more precise and helps improve the matching accuracy. Our pipeline can be incorporated into most existing 2D local image feature detectors and descriptors. We comprehensively evaluate its performance with various experiments on a diversified selection of benchmark datasets. The results show that the majority of tested detectors/descriptors gain additional matching accuracy with proposed pipeline. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10577149
Volume :
29
Database :
Academic Search Index
Journal :
IEEE Transactions on Image Processing
Publication Type :
Academic Journal
Accession number :
170078563
Full Text :
https://doi.org/10.1109/TIP.2020.3013384