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In this paper, we propose an online motion smoothing method.
In this paper, we propose an online motion smoothing method based on linear estimation applied to a constant-velocity model.
In this paper, we propose an online motion smoothing method for video stabilization based on the existing constant-velocity Kalman-filtering method.
In [9], the authors proposed a dual pass motion smoothing method which could find an optimal cropping size with as large as possible.
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Our method is motivated by Kalman-filtering-based motion smoothing with a constant-velocity model.
Therefore, motion smoothing is necessary.
Most existing motion smoothing algorithms are offline smoothing.
This paper focuses on motion smoothing.
Given the estimated camera motion for each frame, motion smoothing aims at designing a new smooth camera motion path.
The results show that this SI method has a better performance than the SE-B estimator [19], while being significantly simpler than frame interpolation with spatial motion smoothing and motion vector refinement [22].
Section 5 shows how motion smoothing is improved using the proposed algorithm of multiple motion models.
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