Slow and Smooth: a Bayesian Theory for the Combination of Local Motion Signals in Human Vision

نویسنده

  • Edward H. Adelson
چکیده

In order to estimate the motion of an object, the visual system needs to combine multiple local measurements , each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements from diierent image regions are combined according to a Bayesian estimator | the estimated motion maximizes the posterior probability assuming a prior favoring slow and smooth velocities. In reviewing a large number of previously published phenomena we nd that the Bayesian estimator predicts a wide range of psychophysical results. This suggests that the seemingly complex set of illusions arise from a single computational strategy that is optimal under reasonable assumptions.

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تاریخ انتشار 1998