Abstract
The camera systems are usually suffered from random jitter. In this paper, a new method based on Kalman filter and homography transformation is proposed to stabilize the unstable video. Firstly, the SURF (Speed-Up Robust Feature) point-feature matching algorithm is employed to find the corresponding matching points between two consecutive frames, and the bidirectional nearest neighbor distance ratio method is used to clear false matches. Secondly, motion estimation is computed by homography model and least square method. Then, Kalman filter are applied to separate the global and local motion. Finally, the unstable video frames is compensated by global motion vector. The experiment result shows that proposed method can effectively eliminate the random jitter.
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Acknowledgments
This work was supported in part by National Natural Science Foundation of China (No. 60972016, No. 61231010), and Funds of Distinguished Young Scientists of China (No. 2009CDA150).
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Liu, C., Li, X., Wu, M. (2018). Video Stabilization Algorithm Based on Kalman Filter and Homography Transformation. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data & Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-59463-7_31
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DOI: https://doi.org/10.1007/978-3-319-59463-7_31
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