Robust Online Digital Image Stabilization Based on Point-Feature Trajectory Without Accumulative Global Motion Estimation

Abstract

A framework of robust online digital image stabilization based on point-feature trajectory is proposed. The conventional online digital image stabilization approaches, which have to use accumulative global motion with respect to the initial reference frame, might fail in the long run because error accumulation is inevitable with the elapse of time. Instead, the proposed scheme directly estimates the correction motion between unstable input and stabilized output images by exploiting original and smoothed point-feature trajectories without the accumulative global motion. As a result, ours is able to operate for a long time. The experimental results show that the proposed method is able to stabilize unstable video with real-time process for a long time and has good robustness to a variety of conditions.