MLBP: MAS for large-scale biometric pattern recognition

Abstract. Security systems can observe and hear almost anyone everywhere. 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 two scenarios to demonstrate the usefulness of the framework. The goal in the first scenario is to point out individuals who visited a sequence of airports, using face recognition algorithms. The goal in the second scenario is to point out individuals who called a set of phones, using speaker recognition algorithms. Theoretical performance analysis and simulation results show a high overall accuracy of our system in real-time.

• Type: Conference
• Year: 2006
• Where: ATAL
• Authors: Ram Meshulam, Shulamit Reches, Aner Yarden, Sarit Kraus
• Keywords: ATAL 2006, Autonomous Multi-agent Framework, Face Recognition Algorithms, Intelligent Agents, Recognition Algorithms