Polarimetric Helmholtz Stereopsis

Yuqi Ding1, Yu Ji2, Mingyuan Zhou, Sing Bing Kang3, Jinwei Ye1,4,
1Louisiana State University, 2Tencent Pixel Lab, 3Zillow Group, 4George Mason University
TPAMI Ver. ICCV Ver. Video Data Supplementary Material

Abstract

In this paper, we present the polarimetric Helmholtz stereopsis (polar-HS), which extends the classical Helmholtz stereopsis by considering the polarization state of light in the reciprocal paths. With the additional phase information from polarization, polar-HS requires only one reciprocal image pair. We formulate new reciprocity and diffuse/specular polarimetric constraints to recover surface depths and normals using an optimization framework. Using a hardware prototype, we show that our approach produces high-quality 3D reconstruction for different types of surfaces, ranging from diffuse to highly specular.

3D Reconstruction Results

Polarimetric Image Decomposition

Polarimetric Image Decomposition.

BibTeX

@ARTICLE {ding2024phs_pami,
  author    = {Ding, Yuqi and Ji, Yu and Cheng, Zhang and Zhou, Mingyuan and Kang, Sing Bing and Ye, Jinwei},
  title     = {Polarimetric Helmholtz Stereopsis},
  journal   = {IEEE Transactions on Pattern Analysis & Machine Intelligence},
  month     = {January},
  year      = {2024},
}
@InProceedings{ding2021phs_iccv,
  author    = {Ding, Yuqi and Ji, Yu and Zhou, Mingyuan and Kang, Sing Bing and Ye, Jinwei},
  title     = {Polarimetric Helmholtz Stereopsis},
  booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
  month     = {October},
  year      = {2021},
}