Statistical efficiency approach to visual representation and object recognition

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This study investigated the ability of human visual system to recognize a 3D object and its representation in the brain by use of a statistical efficiency method. In principle, we added some spatial Gaussian noise to stimuli, and calculated the statistical efficiency with comparing the discriminability of human observer with that of the ideal observer. The results of this research are as follows :(1) We presented wire-frame models of some 3D objects in a computer display and made subjects observe them with the monocular or the stereoscopic view. The results showed that a structure of the object had effects in the discrimination of the object under the stereoscopic vision.(2) We investigated the ''recovery of structure from motion" with use of the efficiency method. The results showed that the recovery of 3D structure from motion was less than that of 2D structure, and suggested that sampling errors occurr in a process of the 3D recovery.(3) We investigated an ability of the visual system to recognize a 3D object overlapped some spatial noises under the stereoscopic condition. It was suggested that, in this situation, a process of grouping of the components could be involved in the object recognition.(4) We investigated the segregation of moving objects from background moving noises with use of the efficiency method. The difference of direction or velocity of the moving object from the background noises was crucial factors in the segregation. The results showed low efficiencies of the visual system in the discrimination of the moving object. This indicated that the visual system samples the motion information with low precision.