Computational model for neural representation of multiple disparities

It has been known that the visual system can detect more than one disparity and/or motion direction at the same region in the image. These multiple (or transparent) surfaces can be perceived when, for example, we are looking scenes through a glass. However, many conventional models cannot deal with...

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Bibliographic Details
Published inNeural networks Vol. 16; no. 1; pp. 25 - 37
Main Authors Watanabe, Osamu, Idesawa, Masanori
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 2003
Elsevier Science
Subjects
Algorithms
Applied sciences
Artificial intelligence
Binocular disparity
Computer science; control theory; systems
Computer Simulation
Connectionism. Neural networks
Energy model
Exact sciences and technology
Models, Neurological
Multiple surfaces
Population
Stereopsis
Transparency
Vision, Binocular - physiology
Visual Perception - physiology
Multiple surfaces
Population
Energy model
Transparency
Stereopsis
Binocular disparity
Biological model
Binocular vision
Disparity
Neural network
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Summary:It has been known that the visual system can detect more than one disparity and/or motion direction at the same region in the image. These multiple (or transparent) surfaces can be perceived when, for example, we are looking scenes through a glass. However, many conventional models cannot deal with these multiple surfaces. The present paper investigates the neural encoding and decoding of multiple disparities with the binocular energy model, which is known as a biologically plausible model. Based on the analysis of the response of the energy model to multiple disparities, the present paper proposes a stereo model that can detect disparities of two overlapping surfaces.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0893-6080
1879-2782
DOI:10.1016/S0893-6080(02)00186-7