Multi-Camera Networks: Principles and Applications

Author:   Hamid Aghajan (Stanford University, USA) ,  Andrea Cavallaro (Queen Mary, University of London, UK)
Publisher:   Elsevier Science Publishing Co Inc
ISBN:  

9780123746337


Pages:   624
Publication Date:   17 June 2009
Format:   Hardback
Availability:   In Print   Availability explained
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Multi-Camera Networks: Principles and Applications


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Overview

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.

Full Product Details

Author:   Hamid Aghajan (Stanford University, USA) ,  Andrea Cavallaro (Queen Mary, University of London, UK)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Dimensions:   Width: 19.10cm , Height: 3.80cm , Length: 23.50cm
Weight:   1.420kg
ISBN:  

9780123746337


ISBN 10:   0123746337
Pages:   624
Publication Date:   17 June 2009
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Preface Introduction Part I: Multi-Camera Calibration and Topology 1. Multiview Geometry for Camera Networks 2. Multiview Calibration Synchronization and Dynamic Scene Reconstruction 3. Actuation-assisted Localization of Distributed Camera Sensor Networks 4. Building an Algebraic Topological Model of Wireless Camera Networks 5. Optimal Placement of Multiple Visual Sensors 6. Optimal Visual Sensor Network Configuration Part II: Active and Heterogeneous Camera Networks 7. Collaborative Control of Active Cameras in Large-Scale Surveillance 8. Pan-Tilt-Zoom Camera Networks 9. Multi-modal Data Fusion Techniques and Applications 10. Spherical Imaging in Omni-directional Camera Networks Part III: Multi-View Coding 11. Video Compression for Camera Networks: a Distributed Approach 12. Distributed Compression in Multi-Camera Systems Part IV: Multi-Camera Human Detection, Tracking, and Pose Analysis 13. On-line Learning a Person Detector by Co-Training from Multiple Cameras 14. Real-time 3D Body Pose Estimation 15. Multi-Person Bayesian Tracking with Multiple Cameras 16. Statistical Pattern Recognition for Multi-Camera Detection, Tracking and Trajectory Analysis 17. Object Association across Multiple Cameras 18. Video Surveillance using a Multi-Camera Tracking and Fusion System 19. Composite Event Detection in Multi-Camera and Multi-Sensor Surveillance Networks Part V: Smart Camera Networks: Architecture, Middleware and Applications 20. Towards Pervasive Smart Camera Networks 21. Smart Cameras for Wireless Camera Networks: Architecture Overview 22. Embedded Middleware for Smart Camera Networks and Sensor Fusion 23. Cluster-Based Object Tracking by Wireless Camera Networks Epilogue: Outlook

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