Fast and Robust Algorithm of Tracking Multiple Moving Objectsfor 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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