Efficient Dense Scene Flow from Sparse or Dense Stereo Data
Abstract
This paper presents a technique for estimating the three-dimensional velocity vector field that describes the motion of each visible scene point (scene flow). The technique presented uses two consecutive image pairs from a stereo sequence. The main contribution is to decouple the position and velocity estimation steps, and to estimate dense velocities using a variational approach. We enforce the scene flow to yield consistent displacement vectors in the left and right images. The decoupling strategy has two main advantages: Firstly, we are independent in choosing a disparity estimation technique, which can yield either sparse or dense correspondences, and secondly, we can achieve frame rates of 5 fps on standard consumer hardware. The approach provides dense velocity estimates with accurate results at distances up to 50 meters.
Cite
Text
Wedel et al. "Efficient Dense Scene Flow from Sparse or Dense Stereo Data." European Conference on Computer Vision, 2008. doi:10.1007/978-3-540-88682-2_56Markdown
[Wedel et al. "Efficient Dense Scene Flow from Sparse or Dense Stereo Data." European Conference on Computer Vision, 2008.](https://mlanthology.org/eccv/2008/wedel2008eccv-efficient/) doi:10.1007/978-3-540-88682-2_56BibTeX
@inproceedings{wedel2008eccv-efficient,
title = {{Efficient Dense Scene Flow from Sparse or Dense Stereo Data}},
author = {Wedel, Andreas and Rabe, Clemens and Vaudrey, Tobi and Brox, Thomas and Franke, Uwe and Cremers, Daniel},
booktitle = {European Conference on Computer Vision},
year = {2008},
pages = {739-751},
doi = {10.1007/978-3-540-88682-2_56},
url = {https://mlanthology.org/eccv/2008/wedel2008eccv-efficient/}
}