SteadyFlow: Spatially Smooth Optical Flow for Video Stabilization

  • Shuaicheng Liu ,
  • Lu Yuan ,
  • Ping Tan ,
  • Jian Sun

IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014) |

Published by IEEE

Publication

We propose a novel motion model, SteadyFlow, to represent the motion between neighboring video frames for stabilization. A SteadyFlow is a specific optical flow by enforcing strong spatial coherence, such that smoothing feature trajectories can be replaced by smoothing pixel pro- files, which are motion vectors collected at the same pixel location in the SteadyFlow over time. In this way, we can avoid brittle feature tracking in a video stabilization system. Besides, SteadyFlow is a more general 2D motion model which can deal with spatially-variant motion. We initialize the SteadyFlow by optical flow and then discard discontinuous motions by a spatial-temporal analysis and fill in missing regions by motion completion. Our experiments demonstrate the effectiveness of our stabilization on real-world challenging videos.