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arXiv · 1608.06800

In the Saddle: Chasing Fast and Repeatable Features

Javier Aldana-Iuit·Dmytro Mishkin·Ondrej Chum·Jiri Matas
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Abstract

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.

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Javier Aldana-Iuit, Dmytro Mishkin, Ondrej Chum, Jiri Matas. 2016-08-24. In the Saddle: Chasing Fast and Repeatable Features. https://arxiv.org/abs/1608.06800

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