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Fast and Robuse Algorithm of Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems

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Fast and Robuse Algorithm of Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems Powered By Docstoc
					  Fast and Robust Algorithm of
Tracking Multiple Moving Objects
for Intelligent Video Surveillance
              Systems

   Jong Sun Kim, Dong Hae Yeom, and
         Young Hoon Joo,2011
                    Goal
• detecting and tracking multiple moving
  objects
• real-time detecting
• robustness against the environmental
  influences and the speed
                    Outline
• Introduction
• Previous Methods
• Detecting Moving Objects
  – Extraction of Moving Objects
  – Grouping Moving Objects
• Tracing Moving Objects
• Implementation and Experiment
• Conclusions
               Introduction
• In the traditional systems that a person should
  always monitor video.
• intelligent video surveillance systems are
  high-cost and low-efficiency
• Environment affects a lot.
• This paper propose a method detecting and
  tracking multiple moving objects in real-time.
           Previous Methods
• particle filter ,extended Kalman filter
• Background modeling (BM) or the Gaussian
  mixture model (GMM)

• gray-scale BM shows the image information is
  excessively attenuated.
    Extraction of Moving Objects
• Using RGB color BM instead of gray-scale BM
• Each pixels will compare with previous pixels
  in little group.
• If it is stationary, the pixels will be black.
• The parameter δ is proposed to overcome the
  sensitivity problem .
• δ would be different on different camera.
Extraction of Moving Objects
Extraction of Moving Objects
Extraction of Moving Objects
      Grouping Moving Objects
• The individual tracking of neighboring or
  overlapping objects requires a lot of
  computational capacity .
• The 4-directional blob-labeling is employed to
  group moving objects.
      Grouping Moving Objects
• Contour Tracing
       Grouping Moving Objects
• its initial search position is set to be
       d+2 (mod 8)
Tracing Moving Objects
Tracing Moving Objects
 Implementation and Experiment
• The 33Mbit IP camera provides the input
  image with 704x480 pixels.
• The surveillance image is transmitted through
  Internet.
• 2.66GHz CPU and 4GB RAM PC for the image
  signal processing and the proposed algorithm.
Implementation and Experiment
Implementation and Experiment
Implementation and Experiment
               Conclusions
• Real-time detecting and tracing
• Only for fixed camera.
• Future works can be on predicted position.

				
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posted:12/19/2011
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