MLBP: MAS for large-scale biometric pattern recognition

Ram Meshulam, Shulamit Reches, Aner Yarden, Sarit Kraus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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 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.

Original languageEnglish
Title of host publicationProceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems
Pages1095-1097
Number of pages3
DOIs
StatePublished - 2006
EventFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS - Hakodate, Japan
Duration: 8 May 200612 May 2006

Publication series

NameProceedings of the International Conference on Autonomous Agents
Volume2006

Conference

ConferenceFifth International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Country/TerritoryJapan
CityHakodate
Period8/05/0612/05/06

Keywords

  • Cooperative distributed problem solving in agent systems
  • Privacy
  • Safety and security in agent systems

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