Studies support the need for high resolution imagery to identify persons in surveillance videos[13]. However, the use of telephoto lenses sacrifices a wider field of view and thereby increases the uncertainty of other, possibly more interesting events in the scene. Using zoom lenses offers the possibility of enjoying the benefits of both wide field of view and high resolution, but not simultaneously. We approach this problem of balancing these finite imaging resources ? or of exploration vs exploitation ? using an informationtheoretic approach. We argue that the camera parameters ? pan, tilt and zoom ? should be set to maximise information gain, or equivalently minimising conditional entropy of the scene model, comprised of multiple targets and a yet unobserved one. The information content of the former is supplied directly by the uncertainties computed using a Kalman Filter tracker, while the latter is modelled using a "background" Poisson process whose parameters are learn...