Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths
Venue
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2011)
Publication Year
2011
Authors
Matthias Grundmann, Vivek Kwatra, Irfan Essa
BibTeX
Abstract
We present a novel algorithm for automatically applying constrainable, L1-optimal
camera paths to generate stabilized videos by removing undesired motions. Our goal
is to compute camera paths that are composed of constant, linear and parabolic
segments mimicking the camera motions employed by professional cinematographers. To
this end, our algorithm is based on a linear programming framework to minimize the
first, second, and third derivatives of the resulting camera path. Our method
allows for video stabilization beyond the conventional filtering of camera paths
that only suppresses high frequency jitter. We incorporate additional constraints
on the path of the camera directly in our algorithm, allowing for stabilized and
retargeted videos. Our approach accomplishes this without the need of user
interaction or costly 3D reconstruction of the scene, and works as a post-process
for videos from any camera or from an online source.
