VERGENCE EYE-MOVEMENT CONTROL AND MULTIVALENT PERCEPTION OF AUTOSTEREOGRAMS

We introduce a dynamical model for automatic vergence eye movement con trol. In connection with our dynamical system of binocular model neuro ns that solves the correspondence problem of stereo-vision, we present a complete model for stereo-vision. Our automatic vergence eye moveme nt control adjusts an image segment, which is of momentary interest to the observer. The adjustment is done in such a way that we only need to define a disparity search range of minimal extension. Recently, a n ew method of encoding (3D) three-dimensional information in 2D picture s was designed in the form of computer-generated patterns of colored d ots. At first glimpse, these so-called autostereograms appear as struc tured but meaningless patterns. After a certain period of observation, a 3D pattern emerges suddenly in an impressive way. Applying our algo rithm to autostereograms, we find a fully satisfactory agreement with the multivalent perception experienced by humans. As in nature, in our model the phase transition between the initial state and the 3D perce ption state takes place in a very short time. Our algorithm is very ro bust against noise, and there is no need to interpolate a sparse depth map.