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Depth Sensing Using Geometrically Constrained Polarization Normals
International Journal of Computer Vision ( IF 11.6 ) Pub Date : 2017-06-22 , DOI: 10.1007/s11263-017-1025-7
Achuta Kadambi , Vage Taamazyan , Boxin Shi , Ramesh Raskar

Analyzing the polarimetric properties of reflected light is a potential source of shape information. However, it is well-known that polarimetric information contains fundamental shape ambiguities, leading to an underconstrained problem of recovering 3D geometry. To address this problem, we use additional geometric information, from coarse depth maps, to constrain the shape information from polarization cues. Our main contribution is a framework that combines surface normals from polarization (hereafter polarization normals) with an aligned depth map. The additional geometric constraints are used to mitigate physics-based artifacts, such as azimuthal ambiguity, refractive distortion and fronto-parallel signal degradation. We believe our work may have practical implications for optical engineering, demonstrating a new option for state-of-the-art 3D reconstruction.

中文翻译:

使用几何约束偏振法线进行深度感应

分析反射光的偏振特性是形状信息的潜在来源。然而,众所周知,极化信息包含基本的形状模糊性,导致恢复 3D 几何的约束不足问题。为了解决这个问题,我们使用来自粗深度图的额外几何信息来约束来自极化线索的形状信息。我们的主要贡献是一个框架,它将来自极化的表面法线(以下称为极化法线)与对齐的深度图相结合。额外的几何约束用于减轻基于物理的伪影,例如方位角模糊、折射失真和前平行信号衰减。我们相信我们的工作可能对光学工程具有实际意义,
更新日期:2017-06-22
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