Phase-based spatio-temporal interpolation for accurate 3D localization in camera networks

Many computer vision applications that exploit a network of independent cameras strongly depend on an accurate synchronization between them. This is indeed the case for 3D tracking. In fact, even if the calibration of the intrinsic and extrinsic parameters of each camera is flawless, inaccurate synchronization would still result in an impaired triangulation between incoherent projective images of the observed features. In many setups, synchronization can be guaranteed with specialized hardware supporting dedicated trigger control lines, however this becomes more difficult when dealing with a (possibly dynamic) network of distributed cameras communicating through wireless channels. With this paper we introduce an end-to-end solution to the problem, including a very simple hardware design for an easy to track device and a practical method that exploits its intrinsic properties for obtaining precise synchronization among an arbitrary number of cameras. Furthermore we propose a simple interpolation schema that can deal naturally with shots captured at different times. Our approach is highly scalable, since it does not require any kind of direct communication or synchronization between cameras. Moreover, new cameras can be added at any time without requiring any additional configuration. In order to test our method we built a specially crafted setup that we used to perform an exhaustive set of experiments.