Bhanu / Ravishankar / Terzopoulos | Distributed Video Sensor Networks | Buch | 978-1-4471-5727-4 | www.sack.de

Buch, Englisch, 485 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 756 g

Bhanu / Ravishankar / Terzopoulos

Distributed Video Sensor Networks


2011
ISBN: 978-1-4471-5727-4
Verlag: Springer

Buch, Englisch, 485 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 756 g

ISBN: 978-1-4471-5727-4
Verlag: Springer


Large-scale video networks are of increasing importance in a wide range of applications. However, the development of automated techniques for aggregating and interpreting information from multiple video streams in real-life scenarios is a challenging area of research.

Collecting the work of leading researchers from a broad range of disciplines, this timely text/reference offers an in-depth survey of the state of the art in distributed camera networks. The book addresses a broad spectrum of critical issues in this highly interdisciplinary field: current challenges and future directions; video processing and video understanding; simulation, graphics, cognition and video networks; wireless video sensor networks, communications and control; embedded cameras and real-time video analysis; applications of distributed video networks; and educational opportunities and curriculum-development.

Topics and features: presents an overview of research in areas of motion analysis, invariants, multiple cameras for detection, object tracking and recognition, and activities in video networks; provides real-world applications of distributed video networks, including force protection, wide area activities, port security, and recognition in night-time environments; describes the challenges in graphics and simulation, covering virtual vision, network security, human activities, cognitive architecture, and displays; examines issues of multimedia networks, registration, control of cameras (in simulations and real networks), localization and bounds on tracking; discusses system aspects of video networks, with chapters on providing testbed environments, data collection on activities, new integrated sensors for airborne sensors, face recognition, and building sentient spaces; investigates educational opportunities and curriculum development from the perspective of computer science and electrical engineering.

This unique text will be of great interest to researchers and graduate students of computer vision and pattern recognition, computer graphics and simulation, image processing and embedded systems, and communications, networks and controls. The large number of example applications will also appeal to application engineers.

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Zielgruppe


Research

Weitere Infos & Material


Introduction

Part I: Distributed Video Sensor Networks and Research Challenges

Report on NSF/ARO/ONR Workshop on Distributed Camera Networks

Part II: Video Processing and Understanding

Motion Analysis

Projective Joint Invariants for Matching Curves in Camera Networks

Multiple-view Object Recognition in Smart Camera Networks

A Comparison of Techniques for Camera Selection and Handoff in a Video Network

Tracking of Multiple Objects Over Camera Networks with Overlapping and Nonoverlapping Views

Toward Robust Online Visual Tracking

Modeling Patterns of Activity and Detecting Abnormal Events with Low-level Co-occurrences

Use of Context in Video Processing

Part III: Simulation, Graphics, Cognition and Video Networks

Virtual Vision

Virtualization and Programming Support for Video Sensor Networks with Application to Wireless and Physical Security

Simulating Human Activities for Synthetic Inputs to Sensor Systems

Cognitive Sensor Networks

Ubiquitous Displays

Part IV: Wireless Video Sensor Networks, Communications and Control

Research Challenges for Wireless Multimedia Sensor Networks

Camera Control and Georegistration for Video Sensor Networks

Persistent Observation of Dynamic Scenes in an Active Camera Network

Proactive PTZ Camera Control

Distributed Consensus Algorithms for Image-based Localization in Camera Sensor Networks

Conditional Posterior Cramér-rao Lower Bound and its Applications in Adaptive Sensor Management

Part V: Distributed Embedded Cameras and Real-Time Video Analysis

VideoWeb

VideoWeb Dataset for Multicamera Activities and Nonverbal Communication

Wide-Area Persistent Airborne Video

Collaborative Face Recognition Using a Network of Embedded Cameras

SATWARE

Part VI: Distributed Video Networks - Applications

Video Analytics For Force Protection

Recognizing Activity Structures in Massive Numbers of Simple Events Over Large Areas

Distributed Sensor Networks for Visual Surveillance

Ascertaining Human Identity in Night Environments

Part VII: Educational Opportunities and Curriculum Development

Educational Opportunities in Video Sensor Networks



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