Real-time video stabilization via camera path correction and its applications to augmented reality on edge devices

With the rapid development of edge devices such as mobile phones, in the past decade, many videos have appeared on the professional video website and they are easy to retrieve. However, most of the videos captured by mobile cameras are jittery, and even motion blurred. These low-quality videos may affect the experience of users. Thus, the problem that how to eliminate the jittery issues, and make unstable video became stable one is very urgent. To enhance the stability of low-quality video, in this paper, we propose a novel method for video stabilization. The proposed method is called SimpleStab, and consists of motion estimation, trajectory smoothing, and compositing image. The SimpleStab is not only able to process offline videos but also can deal with live video streaming due to the novel architecture. We conduct a comprehensive experiment on the benchmarking dataset and make comparison with the state-of-the-art approaches. Experimental results show that the performance of SimpleStab is superior to the state-of-the-art methods.