The effect of stimulus factors such as interobject similarity and stimulus density on the recognition of objects across changes in view was investigated in five experiments. The recognition of objects across views was found to depend on the degree of interobject similarity and on stimulus density: recognition was view dependent when both interobject similarity and stimulus density were high, irrespective of the familiarity of the target object. However, when stimulus density or interobject similarity was low recognition was invariant to viewpoint. It was found that recognition was accomplished through view-dependent procedures when discriminability between objects was low.
The findings are discussed in terms of an exemplar-based model in which the dimensions used for discriminating between objects are optimised to maximise the differences between the objects. This optimisation process is characterised as a perceptual ‘ruler’ which measures interobject similarity by stretching across objects in representational space. It is proposed that the ‘ruler’ optimises the feature differences between objects in such a way that recognition is view invariant but that such a process incurs a cost in discriminating between small feature differences, which results in view-dependent recognition performance.
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