This paper presents an information-driven online video composition system. The composition work handled by the system includes dynamically setting multiple pan/tilt/zoom (PTZ) cameras to proper poses and selecting the best close-up view for passive viewers. The main idea of the composition system is to maximize captured video information with limited cameras. Unlike video composition based on heuristic rules, our video composition is formulated as a process of minimizing distortions between ideal signals (i. e. signals with infinite spatial-temporal resolution) and displayed signals. The formulation is consistent with many well-known empirical approaches widely used in previous systems and may provide analytical explanations to those approaches. Moreover, it provides a novel approach for studying video composition tasks systematically. The composition system allows each user to select a personal close up view. It manages PTZ cameras and a video switcher based on both signal characteristics and users’ view selections. Additionally, it can automate the video composition process based on past users’ view-selections when immediate selections are not available. We demonstrate the performance of this system with real meetings.