Motion Detail Preserving Optical Flow Estimation
Abstract
We discuss the cause of a severe optical flow estimation problem that fine motion structures cannot always be correctly reconstructed in the commonly employed multi-scale variational framework. Our major finding is that significant and abrupt displacement transition wrecks small-scale motion structures in the coarse-to-fine refinement. A novel optical flow estimation method is proposed in this paper to address this issue, which reduces the reliance of the flow estimates on their initial values propagated from the coarser level and enables recovering many motion details in each scale. The contribution of this paper also includes adaption of the objective function and development of a new optimization procedure. The effectiveness of our method is borne out by experiments for both large- and small-displacement optical flow estimation. ©2010 IEEE.
Cite
Text
Xu et al. "Motion Detail Preserving Optical Flow Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010. doi:10.1109/CVPR.2010.5539820Markdown
[Xu et al. "Motion Detail Preserving Optical Flow Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2010.](https://mlanthology.org/cvpr/2010/xu2010cvpr-motion/) doi:10.1109/CVPR.2010.5539820BibTeX
@inproceedings{xu2010cvpr-motion,
title = {{Motion Detail Preserving Optical Flow Estimation}},
author = {Xu, Li and Jia, Jiaya and Matsushita, Yasuyuki},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2010},
pages = {1293-1300},
doi = {10.1109/CVPR.2010.5539820},
url = {https://mlanthology.org/cvpr/2010/xu2010cvpr-motion/}
}