An active vision system for multitarget surveillance in dynamic environments.

Abstract

This paper presents a novel agent-based method for the dynamic coordinated selection and positioning of active-vision cameras for the simultaneous surveillance of multiple objects-of-interest as they travel through a cluttered environment with a-priori unknown trajectories. The proposed system dynamically adjusts not only the orientation but also the position of the cameras in order to maximize the system's performance by avoiding occlusions and acquiring images with preferred viewing angles. Sensor selection and positioning are accomplished through an agent-based approach. The proposed sensing-system reconfiguration strategy has been verified via simulations and implemented on an experimental prototype setup for automated facial recognition. Both simulations and experimental analyses have shown that the use of dynamic sensors along with an effective online dispatching strategy may tangibly improve the surveillance performance of a sensing system.