Real-Time 6d Stereo Visual Odometry with Non-Overlapping Fields of View
Abstract
In this paper, we present a framework for 6D absolute scale motion and structure estimation of a multi-camera system in challenging indoor environments. It operates in real-time and employs information from two cameras with non-overlapping fields of view. Monocular Visual Odometry supplying up-to-scale 6D motion information is carried out in each of the cameras, and the metric scale is recovered via a linear solution by imposing the known static transformation between both sensors. The redundancy in the motion estimates is finally exploited by a statistical fusion to an optimal 6D metric result. The proposed technique is robust to outliers and able to continuously deliver a reasonable measurement of the scale factor. The quality of the framework is demonstrated by a concise evaluation on indoor datasets, including a comparison to accurate ground truth data provided by an external motion tracking system.
Cite
Text
Kazik et al. "Real-Time 6d Stereo Visual Odometry with Non-Overlapping Fields of View." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6247843Markdown
[Kazik et al. "Real-Time 6d Stereo Visual Odometry with Non-Overlapping Fields of View." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/kazik2012cvpr-real/) doi:10.1109/CVPR.2012.6247843BibTeX
@inproceedings{kazik2012cvpr-real,
title = {{Real-Time 6d Stereo Visual Odometry with Non-Overlapping Fields of View}},
author = {Kazik, Tim and Kneip, Laurent and Nikolic, Janosch and Pollefeys, Marc and Siegwart, Roland},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2012},
pages = {1529-1536},
doi = {10.1109/CVPR.2012.6247843},
url = {https://mlanthology.org/cvpr/2012/kazik2012cvpr-real/}
}