"SURF: Speeded Up Robust Features" is a performant scale- and rotation-invariant
interest point detector and descriptor.
It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
This is achieved by
- relying on integral images for image convolutions
- building on the strengths of the leading existing detectors and descriptors (using a Hessian matrix-based measure for the detector, and a distribution-based descriptor)
- simplifying these methods to the essential
This leads to a combination of novel detection, description, and matching steps.