Coherent Background Video Inpainting through Kalman Smoothing along Trajectories

Abstract

Video inpainting consists in recovering the missing or corrupted parts of an image sequence so that the reconstructed sequence looks natural. For each frame, the reconstruction has to be spatially coherent with the rest of the image and temporally with respect to the reconstructions of adjacent frames. Most of existing methods only focus on inpainting foreground objects moving with a periodic motion and consider that the background is almost static. In this paper we address the problem of background inpainting and propose a method that handles dynamic background (illumination changes, moving camera, dynamic textures...). The algorithm starts by applying an image inpainting technique to each frame of the sequence and then temporally smoothes these reconstructions through Kalman smoothing along the estimated trajectories of the unknown points. The computation of the trajectories relies on the estimation of forward and backward dense optical flow fields. Several experiments and comparisons demonstrate the performance of the proposed approach.