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

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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