Combining disparate views of objects: Viewpoint costs are reduced by stereopsis

An issue of central concern in the object recognition literature is whether changes in the viewpoint from which an object is depicted produces systematic costs in performance, or whether performance is (largely) unaffected by such changes. This issue has generated a vigorous and lengthy debate because viewpoint-dependent or viewpoint-independent performance has been seen as a reflection of the underlying object representations. The current experiment shows that the effect of viewpoint differences between objects is strongly affected by whether or not they are depicted with stereoscopic depth, a result that is predicted by neither of the main approaches to object recognition. Instead, it is proposed that viewpoint costs in object recognition experiments are a function of the extent to which the information a subject is provided with generalizes across views, without this holding any necessary implications for the nature of the underlying object representations.