ML Anthology

Uncalibrated Photometric Stereo Under Natural Illumination

Zhipeng Mo, Boxin Shi, Feng Lu, Sai-Kit Yeung, Yasuyuki Matsushita
CVPR 2018
doi:10.1109/CVPR.2018.00310 /cvpr/2018/mo2018cvpr-uncalibrated/

Abstract

This paper presents a photometric stereo method that works with unknown natural illuminations without any calibration object. To solve this challenging problem, we propose the use of an equivalent directional lighting model for small surface patches consisting of slowly varying normals, and solve each patch up to an arbitrary rotation ambiguity. Our method connects the resulting patches and unifies the local ambiguities to a global rotation one through angular distance propagation defined over the whole surface. After applying the integrability constraint, our final solution contains only a binary ambiguity, which could be easily removed. Experiments using both synthetic and real-world datasets show our method provides even comparable results to calibrated methods

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Cite

Text

Mo et al. "Uncalibrated Photometric Stereo Under Natural Illumination." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018. doi:10.1109/CVPR.2018.00310

Markdown

[Mo et al. "Uncalibrated Photometric Stereo Under Natural Illumination." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.](https://mlanthology.org/cvpr/2018/mo2018cvpr-uncalibrated/) doi:10.1109/CVPR.2018.00310

BibTeX

@inproceedings{mo2018cvpr-uncalibrated,
  title     = {{Uncalibrated Photometric Stereo Under Natural Illumination}},
  author    = {Mo, Zhipeng and Shi, Boxin and Lu, Feng and Yeung, Sai-Kit and Matsushita, Yasuyuki},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2018},
  doi       = {10.1109/CVPR.2018.00310},
  url       = {https://mlanthology.org/cvpr/2018/mo2018cvpr-uncalibrated/}
}