Stitching Stabilizer: Two-frame-stitching Video Stabilization for Embedded Systems

TL;DR

This paper introduces a low-cost, real-time two-frame stitching algorithm for video stabilization on embedded systems, enhancing stabilization quality without sacrificing image quality or requiring high computational resources.

Contribution

The paper presents a simple, effective two-frame stitching method that enables real-time, high-quality video stabilization on embedded devices like smartphones.

Findings

Achieves real-time stabilization at 30 FPS for Full HD videos

Produces more natural and strongly stabilized videos than existing solutions

Operates with minimal computational cost suitable for embedded systems

Abstract

In conventional electronic video stabilization, the stabilized frame is obtained by cropping the input frame to cancel camera shake. While a small cropping size results in strong stabilization, it does not provide us satisfactory results from the viewpoint of image quality, because it narrows the angle of view. By fusing several frames, we can effectively expand the area of input frames, and achieve strong stabilization even with a large cropping size. Several methods for doing so have been studied. However, their computational costs are too high for embedded systems such as smartphones. We propose a simple, yet surprisingly effective algorithm, called the stitching stabilizer. It stitches only two frames together with a minimal computational cost. It can achieve real-time processes in embedded systems, for Full HD and 30 FPS videos. To clearly show the effect, we apply it to hyperlapse. Using several clips, we show it produces more strongly stabilized and natural results than the existing solutions from Microsoft and Instagram.