Self-Calibrating Polarising Radiometric Calibration
Abstract
We present a self-calibrating polarising radiometric calibration method. From a set of images taken from a single viewpoint under different unknown polarising angles, we recover the inverse camera response function and the polarising angles relative to the first angle. The problem is solved in an integrated manner, recovering both of the unknowns simultaneously. The method exploits the fact that the intensity of polarised light should vary sinusoidally as the polarising filter is rotated, provided that the response is linear. It offers the first solution to demonstrate the possibility of radiometric calibration through polarisation. We evaluate the accuracy of our proposed method using synthetic data and real world objects captured using different cameras. The self-calibrated results were found to be comparable with those from multiple exposure sequence.
Cite
Text
Teo et al. "Self-Calibrating Polarising Radiometric Calibration." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00299Markdown
[Teo et al. "Self-Calibrating Polarising Radiometric Calibration." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/teo2018cvpr-selfcalibrating/) doi:10.1109/CVPR.2018.00299BibTeX
@inproceedings{teo2018cvpr-selfcalibrating,
title = {{Self-Calibrating Polarising Radiometric Calibration}},
author = {Teo, Daniel and Shi, Boxin and Zheng, Yinqiang and Yeung, Sai-Kit},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2018},
doi = {10.1109/CVPR.2018.00299},
url = {https://mlanthology.org/cvpr/2018/teo2018cvpr-selfcalibrating/}
}