A model of neural network extracting binocular parallax |
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Authors: | Yuzo Hirai Kunihiko Fukushima |
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Affiliation: | 1. Department of Electrical Engineering, Keio University, 832, Hiyoshi, Koh-hoku, 223, Yokohama, Japan 2. NHK Boradcasting Science Research Laboratories, 1-10-11, Kinuta, 157, Setagaya, Tokyo, Japan
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Abstract: | A model of neural network extracting binocular parallax is proposed. It is a multilayered network composed of analog threshold elements. Three types of binocular neurons are included in this model. They are binocular simple neurons, binocular gate neurons and binocular depth neurons. The final layers of this model consist of elements which correspond to the binocular depth neurons. The performance of the model has been simulated on a digital computer. The results of the computer simulation show that every element of this model acts like neurons found in cat's and monkey's visual system and this model extracts binocular parallax caused by simple line components satisfactorily. |
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