Introduction to Intelligent Surveillance

1. Front Matter

   Pages i-xiii

   PDF

2. Introduction

   • Wei Qi Yan

   Pages 1-22

3. Surveillance Data Capturing and Compression

   • Wei Qi Yan

   Pages 23-44

4. Surveillance Data Secure Transmissions

   • Wei Qi Yan

   Pages 45-73

5. Surveillance Data Analytics

   • Wei Qi Yan

   Pages 75-126

6. Biometrics for Surveillance

   • Wei Qi Yan

   Pages 127-153

7. Visual Event Computing I

   • Wei Qi Yan

   Pages 155-165

8. Visual Event Computing II

   • Wei Qi Yan

   Pages 167-179

9. Surveillance Alarm Making

   • Wei Qi Yan

   Pages 181-194

10. Surveillance Computing

    • Wei Qi Yan

    Pages 195-212

11. Back Matter

    Pages 213-222

    PDF

This practically-oriented textbook introduces the fundamentals of designing digital surveillance systems powered by intelligent computing techniques. The text offers comprehensive coverage of each aspect of the system, from camera calibration and data capture, to the secure transmission of surveillance data, in addition to the detection and recognition of individual biometric features and objects. The coverage concludes with the development of a complete system for the automated observation of the full lifecycle of a surveillance event, enhanced by the use of artificial intelligence and supercomputing technology.

This updated third edition presents an expanded focus on human behavior analysis and privacy preservation, as well as deep learning methods.

Topics and features: contains review questions and exercises in every chapter, together with a glossary; describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics; examines the importance of network security and digital forensics in the communication of surveillance data, as well as issues of issues of privacy and ethics; discusses the Viola-Jones object detection method, and the HOG algorithm for pedestrian and human behavior recognition; reviews the use of artificial intelligence for automated monitoring of surveillance events, and decision-making approaches to determine the need for human intervention; presents a case study on a system that triggers an alarm when a vehicle fails to stop at a red light, and identifies the vehicle’s license plate number; investigates the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing.

This concise and accessible work serves as a classroom-tested textbook for graduate-level courses on intelligent surveillance. Researchers and engineersinterested in entering this area will also find the book suitable as a helpful self-study reference.

• Sensor Deployment and Calibrations
• Surveillance Data Encryption and Transmission
• Surveillance Data Analytics and Biometrics
• Surveillance Events and Alarm Making
• Supercomputing in Intelligent Surveillance
• Human Behavior Analysis
• Privacy Preservation
• Deep Learning in Intelligent Surveillance

• Department of Computer Science, Auckland University of Technology, Auckland, New Zealand

  Wei Qi Yan

Dr. Wei Qi Yan is an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title Visual Cryptography for Image Processing and Security.

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