[IPOL announce] new article: Robust Homography Estimation from Local Affine Maps

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2023/356/

Mariano Rodríguez, Gabriele Facciolo, and Jean-Michel Morel,
Robust Homography Estimation from Local Affine Maps,
Image Processing On Line, 13 (2023), pp. 65–89.
https://doi.org/10.5201/ipol.2023.356

Abstract
The corresponding point coordinates determined by classic image matching 
approaches define local zero-order approximations of the global mapping 
between two images. But the patches around keypoints typically contain 
more information, which may be exploited to obtain a first-order 
approximation of the mapping, incorporating local affine maps between 
corresponding keypoints. Several methods have been proposed in the 
literature to compute this first-order approximation. In this paper we 
present several modifications of the RANSAC (RANdom SAmple Consensus) 
algorithm, that uses affine approximations and a-contrario procedures to 
improve the homography estimation between a pair of images. The 
a-contrario methodology provides a definition of the soundness of an 
estimation and allows for adaptive thresholds for inlier/outlier 
discrimination. These approaches outperform the state-of-the-art for 
different choices of image descriptors and image datasets, and permit to 
increase the probability of success in identifying image pairs in 
challenging matching databases.