Online distributed calibration of a large network of wireless cameras using dynamic clustering

We present a cluster-based distributed algorithm for calibrating large networks of wireless cameras. Due to the complex nature of sensing modality of a camera sensor, the work presented here differs significantly from the previous localization methods. Our system does not require any beacon nodes; it only utilizes object features of moving objects in the scene extracted from image sequences. The algorithm is fully distributed, and the localization estimates can be improved as more object features are acquired in the network. We show simulations of our system using a graphical simulator we developed specifically for wireless camera sensor networks. Early results indicate that our system is capable of localizing a large network of cameras in an energy-efficient way.