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.