Surf: Speeded up robust features
In this paper, we present a novel scale-and rotation-invariant interest point detector and
descriptor, coined SURF (Speeded Up Robust Features). 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; by building on the strengths of the leading existing
detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector …
descriptor, coined SURF (Speeded Up Robust Features). 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; by building on the strengths of the leading existing
detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector …
Speeded-up robust features (SURF)
This article presents a novel scale-and rotation-invariant detector and descriptor, coined
SURF (Speeded-Up Robust Features). SURF 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; by building on the strengths of the leading existing detectors and
descriptors (specifically, using a Hessian matrix-based measure for the detector, and a …
SURF (Speeded-Up Robust Features). SURF 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; by building on the strengths of the leading existing detectors and
descriptors (specifically, using a Hessian matrix-based measure for the detector, and a …
