Abstract

With the rapid development of portable digital video equipment, such as camcorders, digital cameras and smart phones, video stabilization techniques for camera de-shaking are strongly required. The cutting-edge video stabilization techniques provide outstanding visual quality by utilizing 3D motion, while early video stabilization is based on 2D motion only. Recently, a content-preserving warping algorithm has been acknowledged as state-of-the-art thanks to its superior stabilization performance. However, the huge computational cost of this technique is a serious burden in spite of its excellent performance. Thus, we propose a fast video stabilization algorithm that provides significantly reduced computational complexity over the state-of-the-art with the same stabilization performance. First, we estimate the 3D information of the feature points in each input frame and define the region of interest (ROI) based on the estimated 3D information. Next, if the number of feature points in the ROI is sufficient, we apply the proposed ROI-based pre-warping and content-preserving warping sequentially to the input frame. Otherwise, conventional full-frame warping is applied. From intensive simulation results, we find that the proposed algorithm reduces computational complexity to 14% of that of the state-of-the-art method, while keeping almost equivalent stabilization performance.

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