Skip to:Content
|
Bottom
Cover image for Multi-camera networks : principles and applications
Title:
Multi-camera networks : principles and applications
Publication Information:
New York : Acad Pr., 2009
Physical Description:
xxvii, 593 p. : ill. ; 25 cm.
ISBN:
9780123746337
Added Corporate Author:

Available:*

Library
Item Barcode
Call Number
Material Type
Item Category 1
Status
Searching...
30000010222268 TK7872.D48 M84 2009 Open Access Book Book
Searching...

On Order

Summary

Summary

The first book, by the leading experts, on this rapidly developing field with applications to security, smart homes, multimedia, and environmental monitoring Comprehensive coverage of fundamentals, algorithms, design methodologies, system implementation issues, architectures, and applications Presents in detail the latest developments in multi-camera calibration, active and heterogeneous camera networks, multi-camera object and event detection, tracking, coding, smart camera architecture and middleware

This book is the definitive reference in multi-camera networks. It gives clear guidance on the conceptual and implementation issues involved in the design and operation of multi-camera networks, as well as presenting the state-of-the-art in hardware, algorithms and system development. The book is broad in scope, covering smart camera architectures, embedded processing, sensor fusion and middleware, calibration and topology, network-based detection and tracking, and applications in distributed and collaborative methods in camera networks. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal and video processing, computer vision, and sensor networks.

Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University. His research is on multi-camera networks for smart environments with application to smart homes, assisted living and well being, meeting rooms, and avatar-based communication and social interactions. He is Editor-in-Chief of Journal of Ambient Intelligence and Smart Environments, and was general chair of ACM/IEEE ICDSC 2008.

Andrea Cavallaro is Reader (Associate Professor) at Queen Mary, University of London (QMUL). His research is on target tracking and audiovisual content analysis for advanced surveillance and multi-sensor systems. He serves as Associate Editor of the IEEE Signal Processing Magazine and the IEEE Trans. on Multimedia, and has been general chair of IEEE AVSS 2007, ACM/IEEE ICDSC 2009 and BMVC 2009.


Table of Contents

Preface
Introduction
Multiview Geometry for Camera Networks
Multiview Calibration Synchronization and Dynamic Scene Reconstruction
Actuation-assisted Localization of Distributed Camera Sensor Networks
Building an Algebraic Topological Model of Wireless Camera Networks
Optimal Placement of Multiple Visual Sensors
Optimal Visual Sensor Network Configuration
Collaborative Control of Active Cameras in Large-Scale Surveillance
Pan-Tilt-Zoom Camera Networks
Multi-modal Data Fusion Techniques and Applications
Spherical Imaging in Omni-directional Camera Networks
Video Compression for Camera Networks: a Distributed Approach
Distributed Compression in Multi-Camera Systems
On-line Learning a Person Detector by Co-Training from Multiple Cameras
Real-time 3D Body Pose Estimation
Multi-Person Bayesian Tracking with Multiple Cameras
Statistical Pattern Recognition for Multi-Camera Detection, Tracking and Trajectory Analysis
Object Association across Multiple Cameras
Video Surveillance using a Multi-Camera Tracking and Fusion System
Composite Event Detection in Multi-Camera and Multi-Sensor Surveillance Networks
Towards Pervasive Smart Camera Networks
Smart Cameras for Wireless Camera Networks: Architecture Overview
Embedded Middleware for Smart Camera Networks and Sensor Fusion
Cluster-Based Object Tracking by Wireless Camera Networks
Epilogue: Outlook
Go to:Top of Page