Scheduling active camera resources for multiple moving targets

Abstract

Five scheduling policies that have been developed and implemented to manage the active resources of a centralized active vision system are presented in this paper. These scheduling policies are tasked with making target-to-camera assignments in an attempt to maximize the number of targets that can be imaged with the system's active cameras. A comparative simulation-based evaluation has been performed to investigate the performance of the system under different target and system operating parameters for all five scheduling policies. Parameters considered include: target entry conditions, congestion levels, target-to-camera speeds, target trajectories, and number of active cameras. An overall trend in the relative performance of the scheduling algorithms was observed. The Least System Reconfiguration and Future Least System Reconfiguration scheduling policies performed the best for the majority of conditions investigated, while the Load Sharing and First Come First Serve policies performed the poorest. The performance of the Earliest Deadline First policy was highly dependent on target predictability.