Real-time video smoothing for small RC helicopters

We present a real-time smoothing methodology for the stabilization of videos captured from small robotic helicopter platforms. We suppress supposedly unintended vibrations considering relative rotation and displacements between successive frames. We propose a similar, an affine or a bilinear transformation to model global motion assuming that camera movement dominates the motion field of aerial footage. A similar model gave worst results in comparison to the others, however all can effectively be employed to stabilize video and should be used depending on particular circumstances. In our implementation all transformations can be estimated by iterative least squares, and an affine model can also be adjusted by a proposed iterative total least squares procedure. Field experiments were carried out with a tele-operated helicopter that transmits wireless video to a receiver in ground where digital smoothing is done. With this configuration we stabilized video at an average speed between 20 and 28 fps, while surpassing problems generated because of the presence of high-levels of noise. We improved our system performance by predicting camera motion and got satisfactory results with even just a small delay of 3 frames. Extending our smoother with more complex vision understanding processes seems straightforward given its flexibility and robustness.