A Multi-Agent Architecture Based on the BDI Model for Data Fusion in Visual Sensor Networks Articles uri icon

publication date

  • junio 2011

start page

  • 299

end page

  • 328

issue

  • 3-4

volume

  • 62

international standard serial number (ISSN)

  • 0921-0296

electronic international standard serial number (EISSN)

  • 1573-0409

abstract

  • The newest surveillance applications is attempting more complex tasks such as the analysis of the behavior of individuals and crowds. These complex tasks may use a distributed visual sensor network in order to gain coverage and exploit the inherent redundancy of the overlapped field of views. This article, presents a Multi-agent architecture based on the Belief-Desire-Intention
    (BDI) model for processing
    the information and fusing the data in a distributed visual sensor
    network. Instead of exchanging
    raw images between the agents involved in the visual
    network, local signal processing is performed and only the key observed
    features are shared. After a registration or calibration
    phase, the proposed architecture performs tracking, data fusion and
    coordination. Using the proposed Multi-agent architecture,
    we focus on the means of fusing the estimated positions on the
    ground plane from different agents which are applied to the
    same object. This fusion process is used for two different purposes:
    (1) to obtain a continuity in the tracking along the field
    of view of the cameras involved in the distributed network, (2)
    to improve the quality of the tracking by means of data
    fusion techniques, and by discarding non reliable sensors.
    Experimental
    results on two different scenarios show that the designed
    architecture can successfully track an object even when occlusions
    or sensor's errors take place. The sensor's errors are
    reduced by exploiting the inherent redundancy of a visual sensor network
    with overlapped field of views.