Statistical Properties in the Visual Decision Process

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The purpose of this research was to calculate the statistical efficiency based on the comparison of the discriminability of Ideal Observer with that of human observer, and to make clear statistical properties of the visual dicision process.The results of this research are as follows.1 We measured the statistical efficiency of detection of three-dimensional mirror symmetry about a sagittal plane. This 3-D mirror symmetry was in the observer centered coordinate system. In order to measure the performance of the Ideal Observer, we introduces a Gaussian noise to the binocular disparity.2 We measured both the statistical efficiency of depth-discrimination between stereoscopically overlapped random-dot surfaces and that of depth-discrimination between two random dot surfaces arrayd side by side. In order to measure the performance of the Ideal Observer, we introduces a Gaussian noise to the binocular disparity.3 We measured the statistical efficiency of discrimination of the motion phase difference between two groups of vertically oscillating random dots. In order to measure the performance of the Ideal Observer, we introduces a Gaussian noise to the motion phase of the oscillating dots.4 We measured the statistical efficiency of discrimination of the motion phase difference between two groups of orthgonally oscillating random dots. In order to measure the performance of the Ideal Observer, we introduces a Gaussian noise to the motion phase of the oscillating dots.5 We measured the statistical efficiency of discrimination between two rigid objects or rigid and nonrigid objects which would be recovered from dot motion. In order to measure the performance of the Ideal Observer, we introduces a Gaussian noise to 3-D position of the moving dots.From these results, we modeled pathway and hierarchical Structure of Visual information Processing.