CVApr 17, 2025

Single-Shot Shape and Reflectance with Spatial Polarization Multiplexing

arXiv:2504.13177v11 citationsh-index: 5
Originality Highly original
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This addresses the challenge of single-shot shape and reflectance recovery for computer vision and graphics, enabling accurate appearance modeling and human interaction without visible patterns.

The paper tackles the problem of recovering object shape and reflectance from a single polarimetric image by proposing spatial polarization multiplexing, achieving reconstruction of shape, Mueller matrix, and BRDF from a single shot with applications to dynamic surfaces.

We propose spatial polarization multiplexing (SPM) for reconstructing object shape and reflectance from a single polarimetric image and demonstrate its application to dynamic surface recovery. Although single-pattern structured light enables single-shot shape reconstruction, the reflectance is challenging to recover due to the lack of angular sampling of incident light and the entanglement of the projected pattern and the surface color texture. We design a spatially multiplexed pattern of polarization that can be robustly and uniquely decoded for shape reconstruction by quantizing the AoLP values. At the same time, our spatial-multiplexing enables single-shot ellipsometry of linear polarization by projecting differently polarized light within a local region, which separates the specular and diffuse reflections for BRDF estimation. We achieve this spatial polarization multiplexing with a constrained de Bruijn sequence. Unlike single-pattern structured light with intensity and color, our polarization pattern is invisible to the naked eye and retains the natural surface appearance which is essential for accurate appearance modeling and also interaction with people. We experimentally validate our method on real data. The results show that our method can recover the shape, the Mueller matrix, and the BRDF from a single-shot polarimetric image. We also demonstrate the application of our method to dynamic surfaces.

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