Video taken in the case of drones and vehicles traveling would be affected by the outside world causing video jitter. This paper proposed to use FAST to obtain the position information of feature points by comparing with the existing electronic image stabilization technology. Then it obtained the position information of the reference frame feature point in the current frame by the optical flow method combined with NCC matching. Based on this, it combined with RANSAC algorithm to eliminate the wrong matching feature points pairs. In order to improve the accuracy of motion vector estimation, this paper applied weighted least squares method to obtain the rigid transformation matrix between adjacent frames. The video was smoothed by Kalman filter to get the motion vector and compensated, and finally got a stable video in real time. The experimental table shows that it improves the fidelity of the inter-frame transform after video sequence stabilization, and achieves the real-time processing speed.

[2019-10-05] Printed Article /doc/2018.05.0355/v2