Machine Learning for High-Speed Corner Detection
نویسندگان
چکیده
Goal A very fast, high quality corner detector. Contributions 1. The segment-test algorithm for detecting features. 2. Machine learning used to create very efficient implementation: the FAST feature detector. 3. Extensive testing of the new detector against existing ones. Results 1. Extremely fast feature detector: uses less than 7% of the available CPU time in live video feeds. 2. Very high quality: FAST outperformed the other detectors in repeatability. 3.Verifiable results: the corner detector and testing datasets are available for download. The Segment-Test Algorithm If ≥ N contiguous pixels in a Bresenham circle of radius r around a centre pixel p are all brighter than p by some threshold or all darker than p by some threshold, then there is a feature at p.
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