Agent-based reconfigurable architecture for real-time object tracking

Most conventional object tracking algorithms are implemented on general-purpose processors in software due to its great flexibility. However, the real-time performance is hard to achieve due to the inherent characteristics of the sequential processing of these processors. To tackle this issue, a reconfigurable system-on-chip (rSoC) platform with microprocessors and FPGAs is applied in this paper. To simplify the hardware/software interface, a Belief–Desire–Intention (BDI)-based multi-agent architecture is proposed as the unified framework. Then an agent-based task graph and two heuristic partitioning methods are proposed to partition the hardware and software on an rSoC platform. Compared to the module-based architecture, this BDI-based multi-agent architecture provides more efficiency, flexibility, autonomy, and scalability for the real-time tracking systems. A particle swarm optimization (PSO)-based object detection and tracking algorithm is applied to evaluate the proposed architecture. Extensive experimental results of object tracking demonstrate that the proposed architecture is efficient and highly robust with real-time performance.