Short-term video stabilization using ground plane segmentation for low altitude UAV object tracking (Conference Presentation)

Fast, efficient and robust algorithms are needed for real-time visual tracking that could also run smoothly on the airborne embedded systems. Flux tensor can be used to provide motion-based cues in visual tracking. In order to use any object motion detection on a raw image sequence captured by a moving platform, the motion caused by the camera movement must be stabilized first. Using feature points to estimate the homography matrix between the frames is a simple registration method that can be used for the stabilization. In order to have a good homography estimation, most of the feature points should lay on the same plane in the images. However, when the scene has complex structures it becomes very challenging to estimate a good homography. In this work, we propose a robust video stabilization algorithm which allows the flux motion detection to efficiently identify moving objects. Our experiments show satisfactory results when other methods shown to fail on the same type of raw videos.