Camera Networks

Camera Networks
The Acquisition and Analysis of Videos over Wide Areas

Amit Roy-Chowdhury, Bi Song
ISBN: 9781608456741 | PDF ISBN: 9781608456758
Copyright © 2012 | 133 Pages | Publication Date: 01/01/2012

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As networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important area of research and technology development. There are many challenges that need to be addressed in the process. Some of them are listed below:

* Traditional computer vision challenges in tracking and recognition, robustness to pose, illumination, occlusion, clutter, recognition of objects, and activities;
* Aggregating local information for wide area scene understanding, like obtaining stable, long-term tracks of objects;
* Positioning of the cameras and dynamic control of pan-tilt-zoom (PTZ) cameras for optimal sensing;
* Distributed processing and scene analysis algorithms;
* Resource constraints imposed by different applications like security and surveillance, environmental monitoring, disaster response, assisted living facilities, etc.

In this book, we focus on the basic research problems in camera networks, review the current state-of-the-art and present a detailed description of some of the recently developed methodologies. The major underlying theme in all the work presented is to take a network-centric view whereby the overall decisions are made at the network level. This is sometimes achieved by accumulating all the data at a central server, while at other times by exchanging decisions made by individual cameras based on their locally sensed data.

Table of Contents

An Introduction to Camera Networks
Wide-Area Tracking
Distributed Processing in Camera Networks
Object and Activity Recognition
Active Sensing
Future Research Directions

About the Author(s)

Amit Roy-Chowdhury, University of California, Riverside
Amit K. Roy-Chowdhury is an Associate Professor of Electrical Engineering and Cooperating Faculty in Computer Science at the University of California, Riverside. He received his PhD from the University of Maryland, College Park, in 2002. His research and teaching interests are in signal and image processing, computer vision and pattern recognition. He has been a Principal Investigator on a number of research projects related to motion analysis in video, camera networks and image analysis for biological applications, and has published over 100 technical articles on these topics.

Bi Song, University of California, Riverside
Bi Song is Sr. Applied Research Engineer at Sony Electronics Inc, San Jose, California. She received her PhD in Electrical Engineering from the University of California, Riverside, in 2009. Her research focus has been on scene analysis in distributed camera networks and motion analysis in video. She has published more than 20 technical papers and book chapters on these topics.

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