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Description: The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving
object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of
RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed
uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system.
These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid-
based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis
to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed.
Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels
but also have a better robustness.
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一种基于主成分分析的Codebook背景建模算法_霍东海.pdf
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