Multi-camera active surveillance of an articulated human form – An implementation strategy

This paper presents an effective framework for real-time reconfiguration of a multi-camera active-vision system performing surveillance of articulated objects with time-varying geometries. The proposed novel real-world strategy tangibly improves surveillance performance by selecting near-optimal viewpoints along a prediction time horizon in order to maximize visibility of a human form in the presence of multiple, dynamic obstacles. Controlled experiments have demonstrated a positive relationship between system re-configurability and surveillance performance.

► Multi-camera active-vision system used to improve human action sensing performance.
► Environment may be cluttered with multiple, dynamic obstacles.
► Selects near-optimal camera poses to maximize visibility of a human subject.
► Generalized framework can be customized to other time-varying-geometry objects.
► Shown to tangibly improve performance in real-world, dynamic environments.