how these scale-invariant feature detectors are formulated). Furthermore, the scale levels obtained from automatic scale selection can be used for determining regions of interest for subsequent affine shape adaptation to obtain affine invariant interest points or for determining scale levels for computing associated image descriptors, such as locally scale adapted N-jets. Recent work has shown that also more complex operations, such as scale-invariant object recognition can be performed in this way, by computing local image descriptors (N-jets or local histograms of gradient directions) at scale-adapted interest points obtained from scale-space extrema of the normalized Laplacian operator (see also scale-invariant feature transform) or the determinant of the Hessian (see also SURF); see also the Scholarpedia article on the scale-invariant feature transform for a more general outlook of object recognition approaches based on receptive field responses in terms Gaussian derivative operators or approximations thereof. Related multi-scale representations An image pyramid is a discrete representation in which a scale space is sampled in both space and scale. For scale invariance, the scale factors should be sampled exponentially, for example as integer powers of 2 or . When properly constructed, the ratio of the sample rates in space and scale are held constant so that the impulse response is identical in all levels of the pyramid. Fast, O(N), algorithms exist for computing a scale invariant image pyramid, in which the image or signal is repeatedly smoothed then subsampled. Values for scale space between pyramid samples can easily be estimated using interpolation within and between scales and allowing for scale and position estimates with sub resolution accuracy. In a scale-space representation, the existence of a continuous scale parameter makes it possible to track zero crossings over scales leading to so-called deep structure. For features defined as zero-crossings of differential invariants, the implicit function theorem directly defines trajectories across scales, and at those scales where bifurcations occur, the local behaviour can be modelled by singularity theory. Extensions of linear scale-space theory concern the formulation of non-linear scale-space concepts more committed to specific purposes. These non-linear scale-spaces often start from the equivalent diffusion formulation of the scale-space concept, which is subsequently extended in a non-linear fashion. A large number of evolution equations have been formulated in this way, motivated by different specific requirements (see the abovementioned book references for further information). It should be noted, however, that not all of these non-linear scale-spaces satisfy similar "nice" theoretical