MLBP: MAS for large-scale biometric pattern recognition

Security systems can observe and hear almost anyone every-where. However, it is impossible to employ an adequate number of human experts to analyze the information explosion. In this paper we present an autonomous multi-agent framework which, as an input, obtains biometric information acquired at a set of locations. The framework aims in real-time to point out individuals who act according to a suspicious pattern across these locations. The system works in large-scale scenarios. We present a scenario to demonstrate the usefulness of the framework. The goal is to point out individuals who visited a sequence of airports using face recognition algorithms. Simulation results show a high overall accuracy of our system in real-time.

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