Image feature points are detected as pixels which locally maximize a detector function, two commonly used examples of which are the (Euclidean) image gradient and the Harris-Stephens corner detector. A major limitation of these feature detectors are that they are only Euclidean-invariant. In this work we demonstrate the application of a 2D affine-invariant image feature point detector based on differential invariants as derived through the equivariant method of moving frames. The fundamental equi-affine differential invariants for 3D image volumes are also computed.
@article{arxiv.1803.01669,
title = {Affine Differential Invariants for Invariant Feature Point Detection},
author = {Stanley L. Tuznik and Peter J. Olver and Allen Tannenbaum},
journal= {arXiv preprint arXiv:1803.01669},
year = {2018}
}