Analog VLSI Circuits for the Perception of Visual Motion

244 Pages·2006·3.5 MB·English

by  Alan A. Stocker

Analog VLSI Circuits for the
Perception of Visual Motion

Analog VLSI Circuits for the
Perception of Visual Motion
Alan A. Stocker
Howard Hughes Medical Institute and Center for Neural Science,
New York University, USA
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LibraryofCongressCataloging-in-PublicationData
Stocker,Alan.
AnalogVLSICircuitsfortheperceptionofvisualmotion/AlanStocker.
p.cm.
Includesbibliographicalreferencesandindex.
ISBN-13:978-0-470-85491-4(cloth:alk.paper)
ISBN-10:0-470-85491-X(cloth:alk.paper)
1.Computervision.2.Motionperception(Vision)–Computersimulation.
3.Neuralnetworks(Computerscience)I.Title.
TA1634.S762006
006.3(cid:1)7–dc22
2005028320
BritishLibraryCataloguinginPublicationData
AcataloguerecordforthisbookisavailablefromtheBritishLibrary
ISBN-13:978-0-470-85491-4
ISBN-10:0-470-85491-X
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Contents
Foreword xi
Preface xiii
1 Introduction 1
1.1 Artificial Autonomous Systems . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Neural Computation and Analog Integrated Circuits . . . . . . . . . . . . . 5
2 Visual Motion Perception 7
2.1 Image Brightness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 Correspondence Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.3 Optical Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.4 Matching Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4.1 Explicit matching. . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4.2 Implicit matching. . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.5 Flow Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.5.1 Global motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.5.2 Local motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.5.3 Perceptual bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.6 Outline for a Visual Motion Perception System . . . . . . . . . . . . . . . . 23
2.7 Review of aVLSI Implementations . . . . . . . . . . . . . . . . . . . . . . 24
3 Optimization Networks 31
3.1 Associative Memory and Optimization . . . . . . . . . . . . . . . . . . . . 31
3.2 Constraint Satisfaction Problems . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3 Winner-takes-all Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.3.1 Network architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.3.2 Global convergence and gain . . . . . . . . . . . . . . . . . . . . . 38
3.4 Resistive Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
4 Visual Motion Perception Networks 45
4.1 Model for Optical Flow Estimation . . . . . . . . . . . . . . . . . . . . . . 45
4.1.1 Well-posed optimization problem . . . . . . . . . . . . . . . . . . . 48
4.1.2 Mechanical equivalent . . . . . . . . . . . . . . . . . . . . . . . . . 49