Timeline-based information assimilation in multimedia surveillance and monitoring systems

  • Authors:

  • Pradeep K. Atrey;Mohan S. Kankanhalli;Ramesh Jain

  • Affiliations:

  • National University of Singapore, Republic of Singapore;National University of Singapore, Republic of Singapore;University of California, Irvine, CA

  • Venue:
  • Proceedings of the third ACM international workshop on Video surveillance & sensor networks
  • Year:
  • 2005

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Abstract

Most surveillance and monitoring systems nowadays utilize multiple types of sensors. However, due to the asynchrony among and diversity of sensors, information assimilation - how to combine the information obtained from asynchronous and multifarious sources is an important and challenging research problem. In this paper, we propose a hierarchical probabilistic method for information assimilation in order to detect events of interest in a surveillance and monitoring environment. The proposed method adopts a bottom-up approach and performs assimilation of information at three different levels - media-stream level, atomic-event level and compound-event level.To detect an event, our method uses not only the current media streams but it also utilizes their two important properties - first, accumulated past history of whether they have been providing the concurring or contradictory evidences, and - second, the system designer's confidence in them. A compound event, which comprises of two or more atomic-events, is detected by first estimating probabilistic decisions for the atomic-events based on individual streams, and then by aligning these decisions along a timeline and hierarchically assimilating them. The experimental results show the utility of our method.