The decreasing cost and size of video sensors has led to camera networks becoming pervasive in our lives. However, the ability to analyze these images effectively is very much a function of the quality of the acquired images. In this paper we consider the problem of automatically controlling the fields of view of individual pan, tilt, zoom (PTZ) cameras in a camera network leading to improved situation awareness (e.g. where and what are the critical targets and events) in a region of interest. The network of cameras attempts to observe the entire region of interest at some minimum resolution while opportunistically acquiring high resolution images of critical events in real time. This is achieved by understanding the performance of video analysis tasks and designing camera control strategies to improve these tasks through the measurement of the quality of the source imagery. Optimization strategies, along with a distributed implementation, are proposed. The proposed methods bring together computer vision and network control ideas. Performance of the proposed methodologies discussed herein have been evaluated on a real life wireless network of pan, tilt and zoom capable cameras.
['Chong Ding', 'Jay A. Farrell', 'Amit K. Roy-Chowdhury']
Capturing high fidelity images in PTZ camera networks