1. A method of identifying candidate interest points in an image having rows and columns of image data, the method comprising: receiving the rows of image data in series; generating downscaled image data by blurring the image data received, wherein the downscaled image data represents the blurred data from a pattern of pixel locations in the received image data; identifying candidate interest points at a first scale by Hessian-filtering the image data and detecting extrema in the Hessian-filtered data; discarding the rows of image data in series; identifying candidate interest points at a second scale by Hessian-filtering the downscaled image data and detecting extrema in the Hessian-filtered, downscaled data, wherein at least one of the rows of image data is discarded before all the rows of image data have been received; generating twice downscaled image data by blurring the downscaled image data, wherein the twice downscaled image data represents the blurred data from a pattern of pixel locations in the once downscaled image data; and detecting candidate interest points at a third scale by Hessian-filtering the twice downscaled image data and detecting extrema in the Hessian-filtered, twice downscaled data.