Automated Multi-Camera Surveillance

Algorithms and Practice

By: Omar Javed, Mubarak Shah

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Hardcover | 3 November 2008

At a Glance

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116 Pages

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24.13 x 15.88 x 1.27

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The recent development of intelligent surveillance systems has captured the interest of both academic research labs and industry. Automated Multi-Camera Surveillance addresses monitoring of people and vehicles, and detection of threatening objects and events in a variety of scenarios. In this book, techniques for development of an automated multi-camera surveillance system are discussed and proposed. The state-of-the-art in the automated surveillance systems is reviewed as well. Detailed explanation of sub-components of surveillance systems are provided, and enhancements to each of these components are proposed. The authors identify important challenges that such a system must address, and propose solutions. Development of a specific surveillance system called "KNIGHT" is described, along with the authors' experience using it. This book enables the reader to understand the mathematical models and algorithms underlying automated surveillance as well as the benefits and limitations of using such methods.

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You Can Find This Book In

Non-Fiction Earth Sciences, Geography, Environment, Planning Geography Geographical Information Systems GIS & Remote Sensing Computing & I.T.Computer Science Artificial Intelligence Computer Vision Graphical & Digital Media Applications Databases Data Capture & Analysis Business Applications

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Paperback

Published: 8th December 2010

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Automated Video Surveillance	p. 1
Introduction	p. 1
Automated Systems for Video Surveillance	p. 2
Automated Surveillance System Tasks and Related Technical Challenges	p. 4
Object Detection and Categorization	p. 4
Tracking	p. 4
Tracking Across Cameras	p. 5
General Challenges	p. 6
Introduction to the Proposed Video Understanding Algorithms for Surveillance	p. 6
Book Organization	p. 9
Identifying Regions of Interest in Image Sequences	p. 11
Introduction	p. 11
General Problems in Background Subtraction	p. 12
Related Work	p. 13
Background Subtraction using Color as a Feature	p. 14
Background Subtraction using Multiple Features	p. 16
Finite State Space Based Background Subtraction	p. 17
Proposed Approach for Background Subtraction	p. 17
Assumptions	p. 18
Pixel Level Processing	p. 18
Region Level Processing	p. 21
Frame-Level Processing	p. 22
Results	p. 22
Discussion	p. 24
Object Detection and Categorization	p. 29
Introduction	p. 29
Problems in Object Categorization	p. 30
Related Work	p. 30
Periodicity Based Categorization	p. 30
Object Categorization using Supervised Classifiers	p. 31
Object Categorization using Weakly Supervised Classifiers	p. 32
Overview of the proposed categorization approach	p. 33
Feature Selection and Base Classifiers	p. 34
The Co-Training Framework	p. 36
Online Learning	p. 37
Co-Training Ability Measurement	p. 39
Results	p. 39
Concluding Remarks	p. 42
Object Tracking in a Single Camera	p. 45
Introduction	p. 45
Related Work	p. 45
Feature Point Tracking Methods	p. 46
Region Tracking Methods	p. 47
Methods to Track People	p. 48
Problems in Tracking 2D silhouettes of People	p. 49
Occlusion	p. 50
Entries and Exits	p. 50
Proposed Approach for Tracking	p. 50
Assumptions	p. 50
Object Tracker	p. 51
Results	p. 52
Discussion	p. 54
Tracking in Multiple Cameras with Disjoint Views	p. 59
Problem Overview and Key Challenges	p. 59
Related Work	p. 61
Multi-Camera Tracking Methods Requiring Overlapping Views	p. 61
Multi-Camera Tracking Methods for Non-Overlapping Views	p. 62
Formulation of the Multi-Camera Tracking Problem	p. 64
Learning Inter-Camera Space-Time Probabilities	p. 66
Estimating Change in Appearances across Cameras	p. 67
The Space of Brightness Transfer Functions	p. 68
Estimation of Inter-Camera BTFs and their Subspace	p. 71
Computing Object Color Similarity Across Cameras Using the BTF Subspace	p. 72
Establishing Correspondences	p. 72
Results	p. 74
Conclusions	p. 81
Knight: Surveillance System Deployment	p. 85
Introduction	p. 85
Deploying Surveillance Systems: Ethical Considerations	p. 85
Knight in Action	p. 86
Conclusion	p. 89
Concluding Remarks	p. 91
What's Next?	p. 91
Tracking Crowds	p. 91
Understanding Complex Human Interaction & Activities	p. 92
The Properties of a Good Surveillance System and How Knight Measures Up	p. 92
References	p. 95
Index	p. 103
Table of Contents provided by Ingram. All Rights Reserved.

Automated Multi-Camera Surveillance

Algorithms and Practice

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

Other Editions and Formats

Paperback

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