Synthesis of Visual Modules from Examples: Learning Hyperacuity

摘要

For any given visual competence, it is tempting to conjecture a specificalgorithm and a corresponding neural circuitry. It has been often implicitly assumed that this machinery may be hardwired in the brain. This extreme point of view, if taken seriously, amy quickly lead to absurd consequences. The underlying reason for the spectacular performance of human subjects in these tasks is that the information sampled by the photoreceptors and relayed to the brain does contain the information necessary for precise localization of image features, since the spacing between photoreceptors and the eye's optics satisfy (in the fovea) the constraints of the sampling theorem. More specifically, it has been shown that, in principle, spatial mechanisms that account for grating resolution are sensitive enough to support hyperacuity-level performance. Furthermore, some of the hyperacuity tasks can be solved by detecting 'secondary' cues such as luminance difference (as in the bisection task) or orientation (as in the detection of vertical vernier stimuli). The detailed structure of the neural circuitry that subserves the detection of these cues, or hyperacuity performance in other tasks is, however, unknown.