Dynamic Neural Field Theory for Motion Perception / Edition 1

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Overview

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.

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Product Details

Table of Contents

Foreword
Preface
1 Introduction 1
I Basic Concepts 7
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
12 Discussion 201
Appendices 209
Bibliography 237
List of symbols 251
Index 253
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