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Abstract:
The view based approach to object recognition relies upon the
co-activation of 2-D pictorial elements or features. This approach is
limited to generalising recognition across transformations of objects in
which considerable physical similarity is present in the stored 2-D
images to which the object is being compared. It is, therefore, unclear
how completely novel views of objects might correctly be assigned to
known views of an object so as to allow correct recognition from any
viewpoint.
The answer to this problem may lie in the fact that in the real world
we are presented with a further cue as to how we should associate these
images, namely that we tend to view objects over extended periods of
time. In this paper, neural network and human psychophysics data on
face recognition are presented which support the notion that
recognition learning can be affected by the order in which images
appear, as well as their spatial similarity.
