Aiming at the issue of low accuracy of rainfall estimation by the machine vision algorithm,a rainfall inversion algorithm based on social surveillance video is proposed.Firstly,the rainfall classification network is adopted to remove the no-rain video.Secondly,the foreground information of rainfall videos is extracted by using the alternating direction method of multipliers (ADMM),and the region of interest (ROI) is chosen by semantic segmentation and background subtraction methods.Thirdly,a Gaussian mixture model (GMM) characterized by gray-scale change and saturation features is constructed to choose the raindrops in ROI.Finally,the raindrop size is calculated according to the perspective imaging relations,and the rainfall is inverted through the meteorological Gamma model.The experimental results show that the rainfall classification accuracy of the method reaches 91.3% in the multi-class weather dataset (MWD) and 77.0% in the real dataset,and the rainfall estimation results are more accurate compared with the existing methods.