In this paper, we study the differential invariants and the invariant heat flow in centro-affine geometry, proving that the latter is equivalent to the inviscid Burgers' equation. Furthermore, we apply the centro-affine invariants to develop an invariant algorithm to match features of objects appearing in images. We show that the resulting algorithm compares favorably with the widely applied scale-invariant feature transform (SIFT), speeded up robust features (SURF), and affine-SIFT (ASIFT) methods.
Cite
@article{arxiv.2003.13842,
title = {Feature Matching and Heat Flow in Centro-Affine Geometry},
author = {Peter J. Olver and Changzheng Qu and Yun Yang},
journal= {arXiv preprint arXiv:2003.13842},
year = {2020}
}