Abstract
A number of recent models of shape recognition assume that the outputs of a lattice of early (V1) spatial filters are mapped directly onto an object representation layer. Although such two-layer networks may be appropriate for face recognition or visually guided motor behavior, a near optimum version of such a model failed to generate the qualitative characteristics of human object recognition data. Hidden layers that represent viewpoint-invariant properties of contours may be required for modeling human object recognition.
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