Data Fusion to Improve Trajectory Tracking in a Cooperative Surveillance Multi-Agent Architecture Articles uri icon

publication date

  • October 2010

start page

  • 243

end page

  • 255

issue

  • 3

volume

  • 11

international standard serial number (ISSN)

  • 1566-2535

electronic international standard serial number (EISSN)

  • 1872-6305

abstract

  • In this paper we present a Cooperative Surveillance Multi-Agent System (CS-MAS) architecture extended to incorporate dynamic coalition formation. We illustrate specific coalition formation using fusion skills. In this case, the fusion
    process is divided into two layers: (i) a global layer in the fusion center,
    which initializes the coalitions and (ii) a local layer within coalitions, where
    a local fusion agent is dynamically instantiated. There are several types of
    autonomous agent: surveillance&-sensor agents, a fusion center agent, a local
    fusion agent, interface agents, record agents, planning agents, etc. Autonomous
    agents differ in their ability to carry out a specific surveillance task. A
    surveillance&-sensor agent controls and manages individual sensors (usually video
    cameras). It has different capabilities depending on its functional complexity
    and limitations related to sensor-specific aspects. In the work presented here
    we add a new autonomous agent, called the local fusion agent, to the CS-MAS
    architecture, addressing specific problems of on-line sensor alignment,
    registration, bias removal and data fusion. The local fusion agent is
    dynamically created by the fusion center agent and involves several
    surveillance&-sensor agents working in a coalition. We show how the inclusion of
    this new dynamic local fusion agent guarantees that, in a video-surveillance
    system, objects of interest are successfully tracked across the whole area,
    assuring continuity and seamless transitions.