Exemplar-based object removal in video using GMM

This paper presents an exemplar-based video inpainting mechanism that restores the area of the removal object, and this mechanism can be further employed to extract the background of videos. The region to be inpainted in video is still in background and moving in foreground. Our method consists of a simple preprocessing stage and video inpainting step. The preprocessing stage consists in constructing Gaussian Mixture Model (GMM) for both background and foreground separately, then make use of GMMs to distinguish background and foreground of the entire video. That saves the time for calculating the optical flow mosaics as many video inpainting algorithms do in the preprocessing step. As for video inpainting, we firstly fill the gap as much as possible by copying information from other frames pixel by pixel, and then inpaint the remaining holes in the background by extending the exemplar-based image inpainting algorithm. Experimental results demonstrate that our method for object removal in video is feasible and effective.