Shape Recognition and Illusory Conjunctions

One way to achieve viewpoint-invariant shape recognition is to impose a canonical, object-based frame of reference on a shape and to describe the positions, sizes and orientations of the shape's features relative to the imposed frame. This compulation can be implemented in a parallel network of neuron-like processors, but the network has a tendency to make errors of a peculiar kind: When presented with several shapes it sometimes perceives one shape in the position of another. The parameters can be carefully tuned to avoid these "illusory conjunctions" in normal circumstances, but they reappear if the visual input is replaced by a random mask before the network has settled down. Treisman and Schmidt (1982) have shown that people make similar errors.

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