Pose Estimation of Ad-Hoc Mobile Camera Networks

An algorithm is proposed for the pose estimation of ad-hoc mobile camera networks with overlapping views. The main challenge is to estimate camera parameters with respect to the 3D scene without any specific calibration pattern, hence allowing for a consistent, camera-independent world coordinate system. The only assumption about the scene is that it contains a planar surface patch of a low-rank texture, which is visible in at least two cameras. Such low-rank patterns are quite common in urban environments. The proposed algorithm consists of three main steps: relative pose estimation of the cameras within the network, followed by the localization of the network within the 3D scene using a low-rank surface patch, and finally the estimation of a consistent scale for the whole system. The algorithm follows a distributed architecture, hence the computing power of the participating mobile devices are efficiently used. The performance and robustness of the proposed algorithm have been analyzed on both synthetic and real data. Experimental results confirmed the relevance and applicability of the method.