Projects / Content-Preserving Warps for Video Stabilization
Content-Preserving Warps for Video Stabilization
Feng Liu| University of Wisconsin-Madison
Michael Gleicher| University of Wisconsin-Madison
Hailin Jin| Adobe Systems, Inc.
Aseem Agarwala| Adobe Systems, Inc.
In this paper, we describe a technique that transforms a video from a hand-held video camera so that it appears as if it were taken with a directed camera motion. Our method can adjust the video to appear as if it were taken from nearby viewpoints, allowing for 3D camera movements to be simulated. By aiming only for perceptual plausibility, rather than accurate reconstruction, we are able to develop algorithms that can effectively recreate dynamic scenes from a single source video. Our technique first recovers the original 3D camera motion and a sparse set of 3D, static scene points using an off-the-shelf structure-from-motion system. Then, a desired camera path is computed either automatically (e.g., by fitting a linear or quadratic path) or interactively. Finally, our technique performs a least-squares optimization that computes a spatially-varying warp from each input video frame into an output frame. The warp is computed to both follow the sparse displacements suggested by the recovered 3D structure, and avoid deforming the content in the video frame. Our experiments on stabilizing challenging videos of dynamic scenes demonstrate the effectiveness of our technique.
References |
Publications |
Content-Preserving Warps for Video Stabilization
ACM Transactions on Graphics (Proc. SIGGRAPH), 28(3)
