A system that controls a set of Pan Tilt Zoom (PTZ) cameras for acquiring close-up imagery of subjects in a surveillance site is presented. The PTZ control is based on the output of a multi-camera, multi-target tracking system operating on a set of fixed cameras, and the main goal is to acquire imagery of subjects for biometrics purposes such as face recognition, or non-facial person identification. For this purpose, this paper introduces an algorithm to address the generic problem of collaboratively controlling a limited number of PTZ cameras to capture an observed number of subjects in an optimal fashion. Optimality is achieved by maximizing the probability of successfully completing the addressed biometrics task, which is determined by an objective function parameterized on expected capture conditions such as distance at which a subject is imaged, angle of capture and several others. Such an objective function serves to effectively balance the number of captures per subject and quality of captures. Qualitative and quantitative experimental results are provided to demonstrate the performance of the system which operates in real-time under real-world conditions on four PTZ and four static CCTV cameras, all of which are processed and controlled via a single workstation.