- 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.
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.
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Table of ContentsPreface; 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
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