  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.
