The resolution at which a sensor network observes the environment is a crucial parameter of performance since it governs the range of applications that are feasible using that network. A higher resolution, in most situations, enables more applications and improves the reliability of existing ones. For science applications for instance, a higher resolution may yield newer insights into the phenomenon than available from lower resolution data. In this poster we discuss a system architecture that uses controlled motion to provide virtual high-resolution in a network of cameras. Several orders of magnitude advantage in resolution is achieved. We discuss several system design choices in the context of our prototype camera network implementation that realizes the proposed architecture. Real world data is collected using our prototype system and used for the evaluation of our proposed methods.