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E-raamat: Automated Multi-Camera Surveillance: Algorithms and Practice

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The deployment of surveillance systems has captured the interest of both the research and the industrial worlds in recent years. The aim of this effort is to increase security and safety in several application domains such as national security, home and bank safety, traffic monitoring and navigation, tourism, and military applications. The video surveillance systems currently in use share one feature: A human operator must monitor them at all times, thus limiting the number of cameras and the area under surveillance and increasing cost. A more advantageous system would have continuous active warning capabilities, able to alert security officials during or even before the happening of a crime. Existing automated surveillance systems can be classified into categories according to:The environment they are primarily designed to observe;The number of sensors that the automated surveillance system can handle;The mobility of sensor.The primary concern of this book is surveillance in an outdoor urban setting, where it is not possible for a single camera to observe the complete area of interest. Multiple cameras are required to observe such large environments. This book discusses and proposes techniques for development of an automated multi-camera surveillance system for outdoor environments, while identifying the important issues that a system needs to cope with in realistic surveillance scenarios. The goal of the research presented in this book is to build systems that can deal effectively with these realistic surveillance needs.
Automated Video Surveillance
1(10)
Introduction
1(1)
Automated Systems for Video Surveillance
2(2)
Automated Surveillance System Tasks and Related Technical Challenges
4(2)
Object Detection and Categorization
4(1)
Tracking
4(1)
Tracking Across Cameras
5(1)
General Challenges
6(1)
Introduction to the Proposed Video Understanding Algorithms for Surveillance
6(3)
Book Organization
9(2)
Identifying Regions of Interest In Image Sequences
11(18)
Introduction
11(1)
General Problems in Background Subtraction
12(1)
Related Work
13(4)
Background Subtraction using Color as a Feature
14(2)
Background Subtraction using Multiple Features
16(1)
Finite State Space Based Background Subtraction
17(1)
Proposed Approach for Background Subtraction
17(5)
Assumptions
18(1)
Pixel Level Processing
18(3)
Region Level Processing
21(1)
Frame-Level Processing
22(1)
Results
22(2)
Discussion
24(5)
Object Detection And Categorization
29(16)
Introduction
29(1)
Problems in Object Categorization
30(1)
Related Work
30(3)
Periodicity Based Categorization
30(1)
Object Categorization using Supervised Classifiers
31(1)
Object Categorization using Weakly Supervised Classifiers
32(1)
Overview of the proposed categorization approach
33(1)
Feature Selection and Base Classifiers
34(2)
The Co-Training Framework
36(3)
Online Learning
37(2)
Co-Training Ability Measurement
39(1)
Results
39(3)
Concluding Remarks
42(3)
Object Tracking In A Single Camera
45(14)
Introduction
45(1)
Related Work
45(4)
Feature Point Tracking Methods
46(1)
Region Tracking Methods
47(1)
Methods to Track People
48(1)
Problems in Tracking 2D silhouettes of People
49(1)
Occlusion
50(1)
Entries and Exits
50(1)
Proposed Approach for Tracking
50(2)
Assumptions
50(1)
Object Tracker
51(1)
Results
52(2)
Discussion
54(5)
Tracking In Multiple Cameras With Disjoint Views
59(26)
Problem Overview and Key Challenges
59(2)
Related Work
61(3)
Multi-Camera Tracking Methods Requiring Overlapping Views:
61(1)
Multi-Camera Tracking Methods for Non-Overlapping Views:
62(2)
Formulation of the Multi-Camera Tracking Problem
64(2)
Learning Inter-Camera Space-Time Probabilities
66(1)
Estimating Change in Appearances across Cameras
67(5)
The Space of Brightness Transfer Functions
68(3)
Estimation of Inter-Camera BTFs and their Subspace
71(1)
Computing Object Color Similarity Across Cameras Using the BTF Subspace
72(1)
Establishing Correspondences
72(2)
Results
74(7)
Conclusions
81(4)
Knight: Surveillance System Deployment
85(6)
Introduction
85(1)
Deploying Surveillance Systems: Ethical Considerations
85(1)
Knight in Action
86(3)
Conclusion
89(2)
Concluding Remarks
91(4)
What's Next?
91(1)
Tracking Crowds
91(1)
Understanding Complex Human Interaction & Activities
92(1)
The Properties of a Good Surveillance System and How Knight Measures Up
92(3)
References 95(8)
Index 103