Improved adaptive Gaussian mixture model for background subtraction

University of Amsterdam

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Abstract

Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient adaptive algorithm using Gaussian mixture probability density. Recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.

Citation impact

1,911
total citations
FWCI
8.43
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100%
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13
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Authors

1

Topics & keywords

Keywords
  • Background subtraction
  • Pixel
  • Computer science
  • Gaussian
  • Subtraction
  • Task (project management)
  • Artificial intelligence
  • Probability density function
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