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DICTA
2003

Background Modeling and Subtraction Using a Local-linear-dependence-based Cauchy Statistical Model

8 years 10 months ago
Background Modeling and Subtraction Using a Local-linear-dependence-based Cauchy Statistical Model
:Many motion object detection algorithms rely on the process of background subtraction, an important technique which is used for detecting changes from a model of the background scene. The background model affects object detecting algorithm tolerating changes in background scene and the granularity of the detected foreground objects. An algorithm using a subtracted background modeling based on Cauchy statistical distribution the purpose of object detecting is presented. The paper concludes that the ratios of the intensity values between background image and current image are fitted to a Cauchy distribution. The Cauchy has much heavier tails and better represents the tails of the histogram than the Gaussian. The Cauchy based method without exponential operation is more cost-efficient than the Gaussian. The proposed approach takes the advantages of the statistic distribution characteristic of pixels and spatial correlativity of the region around a pixel to subtract background. The pape...
Ying Ming, Jingjue Jiang, Jun Ming
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where DICTA
Authors Ying Ming, Jingjue Jiang, Jun Ming
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