A robust video stabilization method for camera shoot in mobile devices using GMM-based motion estimator

Abstract

The application of video stabilization methods to mobile devices with low computing power is an important issue. In this study, we aim to provide a robust video stabilization solution for such mobile devices with limited computing resources. We first propose a fast feature extraction method based on a block-wise gradient. Then, we extract motion information through feature point pairs and rebuild the camera path. Finally, the data were smoothed and the corresponding compensation matrix was calculated to obtain a stable video. However, large foreground objects may lead to incorrect motion estimation. Thus, we propose a fast foreground segmentation method based on GMM for jitter scenes to eliminate foreground features and obtain a more accurate camera trajectory. The experimental results show that the proposed method is robust against large foreground objects and exhibits good real-time performance.