Analog VLSI Circuits for the Perception of Visual Motion

Contents

Foreword

Preface

1 Introduction

1.1 Artificial Autonomous Systems

1.2 Neural Computation and Analog Integrated Circuits

2 Visual Motion Perception

2.1 Image Brightness

2.2 Correspondence Problem

2.3 Optical Flow

2.4 Matching Models

2.4.1 Explicit matching

2.4.2 Implicit matching

2.5 Flow Models

2.5.1 Global motion

2.5.2 Local motion

2.5.3 Perceptual bias

2.6 Outline for a Visual Motion Perception System

2.7 Review of a VLSI Implementations

3 Optimization Networks

3.1 Associative Memory and Optimization

3.2 Constraint Satisfaction Problems

3.3 Winner-takes-all Networks

3.3.1 Network architecture

3.3.2 Global convergence and gain

3.4 Resistive Network

4 Visual Motion Perception Networks

4.1 Model for Optical Flow Estimation

4.1.1 Well-posed optimization problem

4.1.2 Mechanical equivalent

4.1.3 Smoothness and sparse data

4.1.4 Probabilistic formulation

4.2 Network Architecture

4.2.1 Non-stationary optimization

4.2.2 Network conductances

4.3 Simulation Results for Natural Image Sequences

4.4 Passive Non-linear Network Conductances

4.5 Extended Recurrent Network Architectures

4.5.1 Motion segmentation

4.5.2 Attention and motion selection

4.6 Remarks

5 Analog VLSI Implementation

5.1 Implementation Substrate

5.2 Phototransduction

5.2.1 Logarithmic adaptive photoreceptor

5.2.2 Robust brightness constancy constraint

5.3 Extraction of the Spatio-temporal Brightness Gradients

5.3.1 Temporal derivative circuits

5.3.2 Spatial sampling

5.4 Single Optical Flow Unit

5.4.1 Wide-linear-range ...