Omar Javed & Mubarak Shah 
Automated Multi-Camera Surveillance 
Algorithms and Practice

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.

Table des matières

Automated Video Surveillance.- Identifying Regions of Interest in Image Sequences.- Object Detection and Categorization.- Object Tracking in a Single Camera.- Tracking in Multiple Cameras with Disjoint Views.- Knight Surveillance System Deployment.- Concluding Remarks.