English
资源说明：We argue that the study of human vision should be
aimed at determining how humans perform natural
tasks with natural images. Attempts to understand the
phenomenology of vision from artificial stimuli,
although worthwhile as a starting point, can lead to
faulty generalizations about visual systems, because of
the enormous complexity of natural images. Dealing
with this complexity is daunting, but Bayesian inference
on structured probability distributions offers the ability
to design theories of vision that can deal with the
complexity of natural images, and that use ‘analysis by
synthesis’ strategies with intriguing similarities to the
brain. We examine these strategies using recent
examples from computer vision, and outline some
important imlications for cognitive science.
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