In the Saddle: Chasing Fast and Repeatable Features
Not on the map. Why?
Abstract (arXiv)
A novel similarity-covariant feature detector that extracts points whose neighbourhoods, when treated as a 3D intensity surface, have a saddle-like intensity profile. The saddle condition is verified efficiently by intensity comparisons on two concentric rings that must have exactly two dark-to-bright and two bright-to-dark transitions satisfying certain geometric constraints. Experiments show that the Saddle features are general, evenly spread and appearing in high density in a range of images. The Saddle detector is among the fastest proposed. In comparison with detector with similar speed, the Saddle features show superior matching performance on number of challenging datasets.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Aug 2016.
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2 papers.