Question: Background modeling with univariate Gaussian density function using the fifteen consecutive frames. In this model, the density function of each pixel is characterized by mean

Background modeling with univariate Gaussian density function using the fifteen consecutive frames. In this model, the density function of each pixel is characterized by mean and standard deviation values . Display both the mean and standard deviation images.Then take the 5.jpg image as an input to the density functions, and generate a likelihood value for each pixel. Apply a proper threshold to the Gaussian density function outputs to perform moving object segmentation. Display the binary segmented image with the threshold value 0.008. (OpenCV- Python) need code for this question please add comments so that I can understand.

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