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Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception.
This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.
|2||Visual perception of motion||9|
|3||Basic principles of the dynamic approach||29|
|4||Dynamic neural fields||49|
|II||Model for Motion Perception||65|
|5||Dynamic neural field model for motion perception||67|
|6||Necessity of the concepts: Model for the motion quartet||79|
|7||Sufficiency of the concepts: Field model for 2D-motion perception||101|
|8||Relationships: neural fields and computational algorithms||123|
|9||Identification of field models from neurophysiological data||141|
|III||Other Applications of Neural Fields||155|
|10||Neural field model for the motor planning of eye movements||157|
|11||Technical applications of neural fields||173|
|List of symbols||251|