Abstract
The implementation of an adaptive visual system founded on the detection of spatio-temporal invariances is described. It is a layered system inspired by the hierarchical processing in the mammalian ventral visual pathway, and models retinal, early cortical and infero-temporal components. A representation of scenes in terms of slowly varying spatio-temporal signatures is discovered through maximising a measure of temporal predictability. This supports categorisation of the environment by a set of view cells (view-trained units or VTUs [1]) that demonstrate substantial invariance to transformations of viewpoint and scale.
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Bray, A. (2002). An Adaptive Hierarchical Model of the Ventral Visual Pathway Implemented on a Mobile Robot. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_55
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DOI: https://doi.org/10.1007/3-540-36181-2_55
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