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Description: Considering the appearance of illumination variation in outdoor video surveillance, a real-time background
modeling framework, which is also composed of accurate foreground detection, is established. In view of the accuracy
of foreground detection, a threshold based on the histogram of pixel0s intensity di® erence between neighboring frames is
proposed. On account of the real-time background modeling, a fast estimation approach on parameters of autoregressive
model is presented. Considering the adaptability to variable illumination, a texture background model insensitive to
outdoor illumination variation is designed. Thus, a uniform model named auto regression and texture (ART) is obtained.
According to the established con¯ dence intervals with perturbation of pixel s intensity and its local texture, foreground in
scenes with di® erent illumination variations is successfully detected. The experimental results indicate that the framework
is adaptive to and can exactly
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一种适应户外光照变化的背景建模及目标检测方法_赵旭东.pdf
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