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Interactive Motion Analysis for Video Surveillance and Long Term Scene Monitoring

  • Andrew W. Senior
  • YingLi Tian
  • Max Lu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6468)

Abstract

In video surveillance and long term scene monitoring applications, it is a challenging problem to handle slow-moving or stopped objects for motion analysis and tracking. We present a new framework by using two feedback mechanisms which allow interactions between tracking and background subtraction (BGS) to improve tracking accuracy, particularly in the cases of slow-moving and stopped objects. A publish-subscribe modular system that provides the framework for communication between components is described. The robustness and efficiency of the proposed method is tested on our real time video surveillance system. Quantitative performance evaluation is performed on a variety of sequences, including standard datasets. With the two feedback mechanisms enabled together, significant improvement in tracking performance are demonstrated particularly in handling slow moving and stopped objects.

Keywords

video surveillance slow-moving and stopped object tracking motion analysis interaction background subtraction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Andrew W. Senior
    • 1
  • YingLi Tian
    • 2
  • Max Lu
    • 3
  1. 1.Google ResearchNew YorkUSA
  2. 2.Department of Electrical EngineeringThe City College, City University of New YorkNew YorkUSA
  3. 3.IBM Global Technology ServicesHawthorneUSA

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