Image-based object recognition
I will report on recognition experiments with (1) unfamiliar objects, (2) objects embedded in scenes, (3) familiar objects, (4) dynamic objects and (5) cross-modal transfer between visual and haptic recognition. All these experiments show strong viewpoint effects and speak in favor of an image-based representation of objects in which the physical similarity can account for recognition with small viewpoint changes. Recently, together with Guy Wallis we started to look at the importance of temporal similarity on the representation and recognition of objects. Temporal similarity can link many views to one object identify, because different views of objects are usually seen in close succession. To test this hypothesis subjects were presented sequences of novel faces in which the identity of the face changed as the head rotated. The subjects showed a tendency to treat the views as if they were of the same person. The results counter the proposal that object views are recognized simply on the basis of objective, structural components. Instead, they suggest that we are continuously associating views of objects to support later recognition, and that we do so not only on the basis of their physical similarity, but also their correlated appearance in time.