Abstract
A robust digital image stabilization algorithm is proposed using a Kalman filter-based global motion prediction and phase correlation-based motion correction. Global motion is basically estimated by adaptively averaging multiple local motions obtained by phase correlation. The distribution of phase correlation determines a local motion vector, and the global motion is obtained by suitably averaging multiple local motions. By accumulating the global motion at each frame, we can obtain the optimal motion vector that can stabilize the corresponding frame. The proposed algorithm is robust to camera vibration or unwanted movement regardless of object’s movement. Experimental results show that the proposed digital image stabilization algorithm can efficiently remove camera jitter and provide continuously stabilized video.
This research was supported by Korean Ministry of Science and Technology under the National Research lab. Project and by Korean Ministry of Information and Communication under HNRC-ITRC program at Chung-Ang university supervised by IITA.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kwon, O., Shin, J., Paik, J. (2005). Video Stabilization Using Kalman Filter and Phase Correlation Matching. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_18
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DOI: https://doi.org/10.1007/11559573_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
Online ISBN: 978-3-540-31938-2
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