Snapshot: A Self-Calibration Protocol for Camera Sensor Networks

Abstract

A camera sensor network is a wireless network of cameras designed for ad-hoc deployment. The camera sensors in such a network need to be properly calibrated by determining their location, orientation, and range. This paper presents Snapshot, an automated calibration protocol that is explicitly designed and optimized for camera sensor networks. Snapshot uses the inherent imaging abilities of the cameras themselves for calibration and can determine the location and orientation of a camera sensor using only four reference points. Our techniques draw upon principles from computer vision, optics, and geometry and are designed to work with low-fidelity, low-power camera sensors that are typical in sensor networks. An experimental evaluation of our prototype implementation shows that Snapshot yields an error of 1-2.5 degrees when determining the camera orientation and 5-10cm when determining the camera location. We show that this is a tolerable error in practice since a Snapshot-calibrated sensor network can track moving objects to within 11cm of their actual locations. Finally, our measurements indicate that Snapshot can calibrate a camera sensor within 20 seconds, enabling it to calibrate a sensor network containing tens of cameras within minutes.