Abstract

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.

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