In our idealized model of receptive fields, all these receptive fields can be thought of as being present at every position in image space and corresponding to a uniform distribution on a hemisphere.
It will then be shown how a generalization of this theory to be presented next can be used for deriving idealized models of receptive fields by necessity, including new extensions for modelling illumination variations in the intensity domain.
These scale-space models can therefore be regarded as idealized functional and phenomenological models of receptive fields, whose actual realization can then be implemented in different ways depending on available hardware or wetware.
Common models of receptive field center-surround structure assume a spatially overlapping center and surround (DeAngelis et al. 1994; Raiguel et al. 1995; Sceniak et al. 1999; Pack et al. 2005; Roberts et al. 2007).
These observations constrain models of receptive field size and structure among cutaneous sensory neurons, and they raise intriguing questions regarding the cellular and developmental mechanisms responsible for this morphological diversity.
The subject of this article is to describe how structural requirements on the first stages of visual processing as formulated in scale-space theory can be used for deriving idealized models of receptive fields and implications of how these theoretical results can be used when modelling biological vision.
It also provides a basic connection to perceptual grouping of pattern elements and their relational organizations by simple modelling of classical receptive fields (CRFs), tuned to the object size.
To compare this bound with Fig. 1, we recall that here we are dealing with the simplified model of isotropic receptive fields, while in [3] the analysis is performed considering two anisotropic indexes n x and n y.
We note, however, that here we are dealing with a simplified model of isotropic receptive fields, since as we will see this provides enough information for the present study, with the advantage that the results can be stated in a clearer form.
Is it possible to derive a theoretical model of how receptive fields "ought to" respond to visual data?
