Table Of ContentVIDEO SURVEILLANCE
Edited by Weiyao Lin
Video Surveillance
Edited by Weiyao Lin
Published by InTech
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Video Surveillance, Edited by Weiyao Lin
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Contents
Preface IX
Part 1 Overview 1
Chapter 1 Information Management and Video Analytics:
the Future of Intelligent Video Surveillance 3
Bennie Coetzer, Jaco van der Merwe and Bradley Josephs
Chapter 2 Efficient Video Surveillance: Performance
Evaluation in Distributed Video Surveillance Systems 17
Aleksandra Karimaa
Chapter 3 Federalism, Privacy Rights, and Intergovernmental
Management of Surveillance: Legal and Policy Issues 27
Michael W. Hail
Part 2 Video Surveillance Systems,
Frameworks, and Structures 35
Chapter 4 Video Surveillance of Today:
Compressed Domain Object Detection, ONVIF Web Services
Based System Component Communication and Standardized
Data Storage and Export using VSAF – a Walkthrough 37
Houari Sabirin and Gero Bäse
Chapter 5 Realizing Video-Surveillance on Wireless Mesh Networks:
Implementation Issues and Performance Evaluation 55
Giovanni Schembra
Chapter 6 An Application of Quantum Networks
for Secure Video Surveillance 73
Alan Mink, Lijun Ma, Barry Hershman and Xiao Tang
Chapter 7 Cooperative Visual Surveillance Network
with Embedded Content Analysis Engine 99
Shao-Yi Chien and Wei-Kai Chan
VI Contents
Chapter 8 SuperVision: Video Content Analysis
Engine for Videosurveillance Applications 125
Lisa Usai, Francesco Pantisano,
Leonardo G. Vaccaro and Franco Selvaggi
Chapter 9 Multi-Stage Video Analysis Framework 147
Andrzej Czyżewski, Grzegorz Szwoch, Piotr Dalka, Piotr Szczuko,
Andrzej Ciarkowski, Damian Ellwart, Tomasz Merta,
Kuba Łopatka, Łukasz Kulasek and Jędrzej Wolski
Part 3 Object Segmentation, Detection, and Tracking 173
Chapter 10 Background Subtraction
and Lane Occupancy Analysis 175
Erhan A. Ince, Nima S. Naraghi and Saameh G. Ebrahimi
Chapter 11 Block Matching-Based Background Generation
and Non-Rigid Shape Tracking for Video Surveillance 193
Taekyung Kim and Joonki Paik
Chapter 12 Integrating Color and Gradient
into Real-Time Curve Tracking
and Feature Extraction for Video Surveillance 217
Huiqiong Chen and Qigang Gao
Chapter 13 Targets Tracking in the Crowd 231
Cheng-Chang Lien
Chapter 14 Measurement of Pedestrian Traffic Using Feature-based
Regression in the Spatiotemporal Domain 247
Gwang-Gook Lee and Whoi-Yul Kim
Chapter 15 The Management of a Multicamera Tracking System for
Videosurveillance by Using an Agent Based Approach 263
Bethel Atohoun and Cina Motamed
Part 4 Content Analysis and Event Detection
for Video Surveillance 277
Chapter 16 A Survey on Behaviour Analysis
in Video Surveillance Applications 279
Teddy Ko
Chapter 17 Automatic Detection of Unexpected Events
in Dense Areas for Videosurveillance Applications 295
Bertrand Luvison, Thierry Chateau, Jean-Thierry Lapreste,
Patrick Sayd and Quoc Cuong Pham
Contents VII
Chapter 18 Automatic Scenario Recognition for Visual-Surveillance
by Combining Probabilistic Graphical Approaches 321
Ahmed Ziani and Cina Motamed
Chapter 19 A Parallel Non-Linear Surveillance Video Synopsis
System with Operator Eye-Gaze Input 335
Ulas Vural and Yusuf Sinan Akgul
Chapter 20 Video Surveillance for Fall Detection 357
Caroline Rougier, Alain St-Arnaud,
Jacqueline Rousseau and Jean Meunier
Chapter 21 Uncertainty Control for Reliable Video
Understanding on Complex Environments 383
Marcos Zúñiga, François Brémond and Monique Thonnat
Part 5 Advanced Topics 409
Chapter 22 Animal Eyes and Video Imagery 411
Tomasz P. Jannson and Ranjit Pradhan
Chapter 23 Hot Topics in Video Fire Surveillance 443
Verstockt Steven, Van Hoecke Sofie, Tilley Nele,
Merci Bart, Sette Bart, Lambert Peter,
Hollemeersch Charles-Frederik and Van De Walle Rik
Chapter 24 Camera Placement for Surveillance Applications 459
Indu Sreedevi, Nikhil R Mittal,
Santanu Chaudhury and Asok Bhattacharyya
Chapter 25 Real-time Stereo Disparity Map
for Continuous Distance Sensing Applications
- A Method of Sparse Correspondence 475
Kunio Takaya
Preface
Video surveillance is becoming increasingly important in many applications, includ-
ing traffi c control, urban surveillance, home security, environmental monitoring, and
healthcare. With the rapid growth of demand for ubiquitous sensing and security,
great challenges have been raised for designing, transmitt ing, and processing over
video surveillance systems. As such, evolution is changing from the tedious manual
surveillance to the effi cient automatic and intelligent surveillance. And this evolu-
tion, in turn, is issuing new challenges in front of us, including system designing, data
analysis and processing, resource scheduling, and data streaming. This requires bet-
ter understanding of the implications of communication, compression, data mining,
content-based video retrieval, machine learning, and patt ern recognition.
The goal of this book is to consolidate and highlight the latest achievements and de-
velopments in the fi eld of video surveillance. The papers selected for this book com-
prise a cross-section of topics that refl ect a variety of perspectives and disciplinary
backgrounds. Besides the introduction of new achievements in video surveillance, this
book also presents some good overviews of the state-of-the-art technologies as well as
some interesting advanced topics related to video surveillance. I believe the 25 chap-
ters presented in this book can provide a clear picture of the current research status in
the area of video surveillance.
This book contains a total of fi ve major parts that cover the following directions: over-
view of the current developments in video surveillance; new designs and frameworks
for video surveillance systems; novel algorithms for object extraction and tracking;
new methods for video content analysis and event detection; and some advanced top-
ics related to video surveillance.
The brief outline of the book is as follows:
Part I presents tutorials, surveys and comparative studies of several new trends and
developments in video surveillance. Chapter 1 is a tutorial on video analysis and infor-
mation management techniques used for video surveillance applications. These two
parts are normally indentifi ed as the key factors for future intelligent video surveil-
lance systems. Chapter 2 gives an overview of the techniques about performance eval-
uation in distributed video surveillance systems. By discussing the evaluation metrics
for various parts including data acquisition, system intelligence, system architecture,
user-interface, and user-oriented functionality, this chapter also provides a clear view
on where and how to improve the effi ciency of a video surveillance system. Chapter 3
X Preface
describes the legal and policy issues for surveillance applications. While surveillance
applications are oft en weighed against the civil rights of individuals being observed,
this chapter gives a very good discussion on this complex rights-and-security balance
issue. Thus, it can serve as a good reference during the practical usage of surveillance
systems.
Part II comprising six chapters is devoted to the design of video surveillance systems,
frameworks, and structures. Here the readers can fi nd a wide variety of surveillance
systems and frameworks for diff erent applications. Chapter 4 provides a walkthrough
to the ONVIF (Open Network Video Interface Forum) video surveillance system, from
the camera through analysis and storage right up to display and export. In addition,
this chapter also illustrates the general trend towards processing increasing amounts
of data in real-time automatically by avoiding completely the task of decoding the vid-
eo prior analysis. Chapter 5 describes a real experience of a wireless video-surveillance
system, illustrating the overall architecture and the structure of each component block.
Specifi cally, video sources use rate-control to emit a constant bit-rate fl ow, while the ac-
cess network is a WMN (Wireless Mesh Networks) implementing a multipath routing
algorithm to minimize delay and intrusions. Furthermore, analysis is also carried out
against the emission bit rate, and quality perceived at destination is evaluated with an
objective parameter. Chapter 6 discusses the QKD (Quantum Key Distribution) proto-
col and its potential to secure video surveillance applications. This chapter shows ex-
amples of a QKD implementation along with reference to other implementations as well
as some innovations that can reduce QKD costs, limit some of the side channel att acks
and provide hardware support to off load CPU processing. In addition it also touched
on the need for integration with existing network infrastructure, providing services
necessary for deployment and an on-going standards eff ort that is needed by both cus-
tomers and developers. Chapter 7 discusses the data abstraction hierarchy and the sys-
tem confi guration of the next-generation surveillance systems. A conclusion has been
made that each camera should be embedded with content analysis ability to become a
smart camera instead of just an IP camera. Furthermore, two examples of cooperative
surveillance systems are also provided for diff erent scenarios. Chapter 8 describes a
video analysis engine called SuperVision system that can analyze video streams from
diff erent types of camera, in particular omnidirectional, and to set alarms when pre-
confi gured events are detected. The types of events detected are numerous, and can
be composed according to the context and needs of applications. Chapter 9 proposes
a multi-stage video analysis framework which is a fl exible and effi cient solution for
automatic analysis of camera images in the monitoring systems.
Part III comprises six chapters and deals with new methods and techniques for object
segmentation, detection, and tracking in videos. Chapter 10 summarizes the existing
techniques for background subtraction and its application in lane occupancy analy-
sis. By comparing diff erent background subtraction methods, this chapter provides a
good insight into the usability and eff ectiveness for various background subtraction
algorithms. Chapter 11 presents a combined shape and feature-based object tracking
method. The proposed method adaptively generates background, which serves as a
fundamental building block for robust tracking by resolving inherent problems of
existing block-matching algorithm. Aft er generating background, the shape tracking
module in the proposed algorithm determines object’s moving region based on shape
control points. Experimental results demonstrate the eff eictiveness of the this method.
