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Helmholtz stereopsis (HS) exploits the reciprocity principle of light propagation (i.e., the Helmholtz reciprocity) for 3D reconstruction of surfaces with arbitrary reflectance. In this paper, we present the polarimetric Helmholtz stereopsis (polar-HS), which extends the classical HS by considering the polarization state of light in the reciprocal paths. With the additional phase information from polar- ization, polar-HS requires only one reciprocal image pair. We formulate new reciprocity and diffuse/specular polari- metric constraints to recover surface depths and normals using an optimization framework. Using a hardware proto- type, we show that our approach produces high-quality 3D reconstruction for different types of surfaces, ranging from diffuse to highly specular.
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Snapshot polarimetric diffuse-specular separation
We present a polarization-based approach to perform diffuse-specular separation from a single polarimetric image, acquired using a flexible, practical capture setup. Our key technical insight is that, unlike previous polarization-based separation methods that assume completely unpolarized diffuse reflectance, we use a more general polarimetric model that accounts for partially polarized diffuse reflections. We capture the scene with a polarimetric sensor and produce an initial analytical diffuse-specular separation that we further pass into a deep network trained to refine the separation. We demonstrate that our combination of analytical separation and deep network refinement produces state-of-the-art diffuse-specular separation, which enables image-based appearance editing of dynamic scenes and enhanced appearance estimation.
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- PAR ID:
- 10370755
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optics Express
- Volume:
- 30
- Issue:
- 19
- ISSN:
- 1094-4087; OPEXFF
- Format(s):
- Medium: X Size: Article No. 34239
- Size(s):
- Article No. 34239
- Sponsoring Org:
- National Science Foundation
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