Title :
A dual CNN model of cyclopean perception and its application potentials in artificial steropsis
Author_Institution :
Comput. & Autom. Inst., Acad. of Sci., Budapest, Hungary
Abstract :
Random-dot stereograms coding 3-D information in their internal correlation are used for probing human stereopsis. Dual cellular neural net (CNN) algorithms that can reveal 3-D surfaces coded in stereograms are reported. The concept of the difference stereogram is introduced and used for coding smooth surfaces. Its importance is due to the fact that difference stereograms of real objects can be created in an optical environment using a projector and camera
Keywords :
cellular arrays; neural nets; physiological models; stereo image processing; visual perception; 3D information coding; artificial steropsis; cellular neural net; cyclopean perception; difference stereogram; dual CNN algorithms; human stereopsis; random-dot stereograms; Application software; Automation; Cameras; Cellular neural networks; Humans; Image segmentation; Laboratories; Retina; Testing; Visual system;
Conference_Titel :
Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
Conference_Location :
Munich
Print_ISBN :
0-7803-0875-1
DOI :
10.1109/CNNA.1992.274365