Affine Differential Invariants for Invariant Feature Point Detection
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Mar 2018.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.
2 papers.
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- 2022Deep Signatures -- Learning Invariants of Planar Curvescited by 1
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