Electronic Image Stabilization based on Motion Classification
Juanjuan Zhu, Baolong Guo
Available Online November 2013.
- https://doi.org/10.2991/icmt-13.2013.180How to use a DOI?
- electronic image stabilization, global motion estimation, motion compensation, feature points
- A novel electronic image stabilization based on motion classification is presented. It achieves image stabilization with high accuracy in complicated camera motion. Firstly, the feature points are selected evenly using the Harris operator and then matched based on the feature window. Hence, the corresponding points are obtained and the statistic features of their motions are analyzed according to different motion kinds including translation, rotation and zoom. Then, the fast motion classification method is proposed to validate all points and delete mismatched or unreliable points. Thirdly, the remained global feature points are brought to the affine model to compute global motion. Lastly, the Kalman filter is used to obtain dithering motion and each current frame is compensated. Experimental results show that the algorithm can correctly detect global motion in dynamic scenes with camera scan and various dithering. Furthermore, its estimation error is below 1/2 pixel and it also accomplishes real-time stabilization, which can greatly improve the stability and fidelity of videos.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Juanjuan Zhu AU - Baolong Guo PY - 2013/11 DA - 2013/11 TI - Electronic Image Stabilization based on Motion Classification BT - 3rd International Conference on Multimedia Technology(ICMT-13) PB - Atlantis Press SP - 1466 EP - 1473 SN - 1951-6851 UR - https://doi.org/10.2991/icmt-13.2013.180 DO - https://doi.org/10.2991/icmt-13.2013.180 ID - Zhu2013/11 ER -