Video Tracking Theory and Practice 2011视频跟踪新书.pdf

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VIDEO TRACKING

Contents

Foreword

About the authors

Preface

Acknowledgements

Notation

Acronyms

1 What is video tracking?

1.1 Introduction

1.2 The design of a video tracker

1.2.1 Challenges

1.2.2 Main components

1.3 Problem formulation

1.3.1 Single-target tracking

1.3.2 Multi-target tracking

1.3.3 Definitions

1.4 Interactive versus automated tracking

1.5 Summary

2 Applications

2.1 Introduction

2.2 Media production and augmented reality

2.3 Medical applications and biological research

2.4 Surveillance and business intelligence

2.5 Robotics and unmanned vehicles

2.6 Tele-collaboration and interactive gaming

2.7 Art installations and performances

2.8 Summary

References

3 Feature extraction

3.1 Introduction

3.2 From light to useful information

3.2.1 Measuring light

3.2.2 The appearance of targets

3.3 Low-level features

3.3.1 Colour

3.3.2 Photometric colour invariants

3.3.3 Gradient and derivatives

3.3.4 Laplacian

3.3.5 Motion

3.4 Mid-level features

3.4.1 Edges

3.4.2 Interest points and interest regions

3.4.3 Uniform regions

3.5 High-level features

3.5.1 Background models

3.5.2 Object models

3.6 Summary

References

4 Target representation

4.1 Introduction

4.2 Shape representation

4.2.1 Basic models

4.2.2 Articulated models

4.2.3 Deformable models

4.3 Appearance representation

4.3.1 Template

4.3.2 Histograms

4.3.3 Coping with appearance changes

4.4 Summary

References

5 Localisation

5.1 Introduction

5.2 Single-hypothesis methods

5.2.1 Gradient-based trackers

5.2.2 Bayes tracking and the Kalman filter

5.3 Multiple-hypothesis methods

5.3.1 Grid sampling

5.3.2 Particle filter

5.3.3 Hybrid methods

5.4 Summary

References

6 Fusion

6.1 Introduction

6.2 Fusion strategies

6.2.1 Tracker-level fusion

6.2.2 Measurement-level fusion

6.3 Feature fusion in a Particle Filter

6.3.1 Fusion of likelihoods

6.3.2 Multi-feature resampling

6.3.3 Feature reliability

6.3.4 Temporal smoothing

6.3.5 Example

6.4 Summary

References

7 Multi-target management

7.1 Introduction

7.2 Measurement validation

7.3 Data association

7.3.1 Nearest neighbour

7.3.2 Graph matching

7.3.3 Multiple-hypothesis tracking

7.4 Random Finite Sets for tracking

7.5 Probabilistic Hypothesis Density filter

7.6 The Particle PHD filter

7.6.1 Dynamic and observation models

7.6.2 Birth and clutter models

7.6.3 Importance sampling

7.6.4 Resampling

7.6.5 Particle clustering

7.6.6 Examples

7.7 Summary

References

8 Context modeling

8.1 Introduction

8.2 Tracking with context modelling

8.2.1 Contextual information

8.2.2 Influence of the context

8.3 Birth and clutter intensity estimation

8.3.1 Birth density

8.3.2 Clutter density

8.3.3 Tracking with contextual feedback

8.4 Summary

References

9 Performance evaluation

9.1 Introduction

9.2 Analytical versus empirical methods

9.3 Ground truth

9.4 Evaluation scores

9.4.1 Localisation scores

9.4.2 Classification scores

9.5 Comparing trackers

9.5.1 Target life-span

9.5.2 Statistical significance

9.5.3 Repeatibility

9.6 Evaluation protocols

9.6.1 Low-level protocols

9.6.2 High-level protocols

9.7 Datasets

9.7.1 Surveillance

9.7.2 Human-computer interaction

9.7.3 Sport analysis

9.8 Summary

References

Epilogue

Further reading

Appendix A Comparative results

A.1 Single versus structural histogram

A.1.1 Experimental setup

A.1.2 Discussion

A.2 Localisation algorithms

A.2.1 Experimental setup

A.2.2 Discussion

A.3 Multi-feature fusion

A.3.1 Experimental setup

A.3.2 Reliability scores

A.3.3 Adaptive versus non-adaptive tracker

A.3.4 Computational complexity

A.4 PHD filter

A.4.1 Experimental setup

A.4.2 Discussion

A.4.3 Failure modalities

A.4.4 Computational cost

A.5 Context modelling

A.5.1 Experimental setup

A.5.2 Discussion

References

Index

RED BOX RULES ARE FOR PROOF STAGE ONLY. DELETE BEFORE FINAL PRINTING. VIDEO TRACKING THEORY AND PRACTICE EMILIO MAGGIO, Vicon, UK ANDREA CAVALLARO, Queen Mary University of London, UK Video Tracking provides a comprehensive treatment of the fundamental aspects of algorithm and application development for the task of estimating, over time, the position of objects of interest seen through cameras. Starting from the general problem deﬁ nition and a review of existing and emerging video tracking applications, the book discusses popular methods, such as those based on correlation and gradient-descent. Using practical examples, the reader is introduced to the advantages and limitations of deterministic approaches, and is then guided toward more advanced video tracking solutions, such as those based on the Bayes’ recursive framework and on Random Finite Sets. KEY FEATURES: Discusses the design choices and implementation issues required to turn the underlying mathematical models into real-world effective tracking systems. Provides block diagrams and simil-code implementation of the algorithms. Reviews methods to evaluate the performance of video trackers – this is identiﬁ ed as a major problem by end-users. The book aims to help researchers and practitioners develop techniques and solutions based on the potential of video tracking applications. The design methodologies discussed throughout the book provide guidelines for developers in the industry working on vision-based applications. The book may also serve as a reference for engineering and computer science graduate students involved in vision, robotics, human-computer interaction, smart environments and virtual reality programmes. MAGGIO CAVALLARO I V D E O T R A C K N G I EMILIO MAGGIO | ANDREA CAVALLARO VIDEO TRACKING THEORY AND PRACTICE

P1: OSO fm JWST014-Cavallaro October 19, 2010 9:12 Printer Name: Yet to Come

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come VIDEO TRACKING

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come VIDEO TRACKING Theory and Practice Emilio Maggio Vicon, UK Andrea Cavallaro Queen Mary University of London, UK A John Wiley and Sons, Ltd., Publication

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come This edition ﬁrst published 2011 C 2011, John Wiley & Sons, Ltd Registered oﬃce John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom For details of our global editorial oﬃces, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our websiteatwww.wiley.com. The right of the author to be identiﬁed as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Library of Congress Cataloging-in-Publication Data Cavallaro, Andrea. Video tracking : theory and practice / Andrea Cavallaro, Emilio Maggio. p. cm. Includes bibliographical references and index. ISBN 978-0-470-74964-7 (cloth) 1. Video surveillance. TK6680.3.C38 2010 621.38928–dc22 2. Automatic tracking. I. Maggio, Emilio. II. Title. 2010026296 A catalogue record for this book is available from the British Library. Print ISBN: 978-0-4707-4964-7 ePDF ISBN: 978-0-4709-7438-4 oBook ISBN: 978-0-4709-7437-7 Set in 10/12pt cmr by Aptara Inc., New Delhi, India.

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come CONTENTS Foreword About the authors Preface Acknowledgements Notation Acronyms 1 What is video tracking? 1.1 1.2 1.3 1.4 1.5 Challenges Introduction The design of a video tracker 1.2.1 1.2.2 Main components Problem formulation 1.3.1 Single-target tracking 1.3.2 Multi-target tracking 1.3.3 Interactive versus automated tracking Summary Deﬁnitions xi xv xvii xix xxi xxiii 1 1 2 2 6 7 7 10 11 12 13 v

P1: OSO fm JWST014-Cavallaro November 12, 2010 15:22 Printer Name: Yet to Come CONTENTS Introduction Applications 2.1 2.2 Media production and augmented reality 2.3 Medical applications and biological research 2.4 2.5 2.6 2.7 2.8 Surveillance and business intelligence Robotics and unmanned vehicles Tele-collaboration and interactive gaming Art installations and performances Summary References vi 2 3 4 3.3 3.5 3.6 The appearance of targets Feature extraction Introduction 3.1 From light to useful information 3.2 3.2.1 Measuring light 3.2.2 Low-level features 3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 Motion Colour Photometric colour invariants Gradient and derivatives Laplacian 3.4 Mid-level features Edges Interest points and interest regions Uniform regions 3.4.1 3.4.2 3.4.3 High-level features 3.5.1 3.5.2 Summary References Background models Object models Target representation 4.1 4.2 Introduction Shape representation 4.2.1 Basic models Articulated models 4.2.2 4.2.3 Deformable models 15 15 16 17 20 21 22 22 23 24 27 27 28 28 30 32 32 39 42 47 49 50 50 51 56 61 62 63 65 65 71 71 72 72 73 74

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