Binocular interaction neural network model using parallel channel architecture

Thomas Y. P. Lee; Clark C. Guest

doi:10.1117/12.157028

23 September 1993 Binocular interaction neural network model using parallel channel architecture

Thomas Y. P. Lee, Clark C. Guest

Proceedings Volume 1915, Stereoscopic Displays and Applications IV; (1993) https://doi.org/10.1117/12.157028
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

Stereo vision is the sensation of visual depth that results from the neural response to dissimilarities in the images seen by the two retinas. Psychophysical studies have strongly suggested that stereo disparity exists in the human visual system, and forms the basis for three-dimensional depth perception in the brain. In the past, this subject has been studied by many scientists using various approaches. Recently, several vision biologists have proposed a human binocular neural interaction model. We derive the mathematical equations for the model based on their discovery, and simulate this multilayer neural network model with real binocular images on a digital computer. This model proves to be a novel approach that provides binocular depth performance close to the biological data.

Citation Download Citation

Thomas Y. P. Lee and Clark C. Guest "Binocular interaction neural network model using parallel channel architecture", Proc. SPIE 1915, Stereoscopic Displays and Applications IV, (23 September 1993); https://doi.org/10.1117/12.157028

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