A Branch-and-Bound Algorithm for Globally Optimal Calibration of a Camera-and-Rotation-Sensor System
Abstract
We propose a branch-and-bound algorithm to obtain the globally optimal relative rotation between a camera and the rotation sensor attached to it. Compared to previous methods, our approach directly minimizes the image space error related to the measurements which is very natural for camera-based systems. Our algorithm is based on the observation that we may evaluate the residual when the rotation matrix is known. We propose a feasibility test algorithm for the branch-and-bound to efficiently reduce the search volume of the rotation domain. Experimental results are provided using synthetic and real data sets.
Cite
Text
Seo et al. "A Branch-and-Bound Algorithm for Globally Optimal Calibration of a Camera-and-Rotation-Sensor System." IEEE/CVF International Conference on Computer Vision, 2009. doi:10.1109/ICCV.2009.5459343Markdown
[Seo et al. "A Branch-and-Bound Algorithm for Globally Optimal Calibration of a Camera-and-Rotation-Sensor System." IEEE/CVF International Conference on Computer Vision, 2009.](https://mlanthology.org/iccv/2009/seo2009iccv-branch/) doi:10.1109/ICCV.2009.5459343BibTeX
@inproceedings{seo2009iccv-branch,
title = {{A Branch-and-Bound Algorithm for Globally Optimal Calibration of a Camera-and-Rotation-Sensor System}},
author = {Seo, Yongduek and Choi, Youngju and Lee, Sang Wook},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2009},
pages = {1173-1178},
doi = {10.1109/ICCV.2009.5459343},
url = {https://mlanthology.org/iccv/2009/seo2009iccv-branch/}
}