Abstract. We propose a novel algorithm for stabilizing selfie videos.
Our goal is to automatically generate stabilized video that has optimal
smooth motion in the sense of both foreground and background. The
key insight is that non-rigid foreground motion in selfie videos can be
analyzed using a 3D face model, and background motion can be analyzed using optical flow. We use second derivative of temporal trajectory
of selected pixels as the measure of smoothness. Our algorithm stabilizes selfie videos by minimizing the smoothness measure of the background, regularized by the motion of the foreground. Experiments show
that our method outperforms state-of-the-art general video stabilization
techniques in selfie videos.