Depth Sensing Using Geometrically Constrained Polarization Normals

Kadambi, Achuta; Taamazyan, Vage; Shi, Boxin; Raskar, Ramesh

doi:10.1007/s11263-017-1025-7

Cited by 67 publications

(24 citation statements)

References 57 publications

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“…More than two views have been used in [20]. Space carving [75,76] or RGBD sensors [57,58] have been employed to obtain initial 3D-shape, from which the ambiguities in SfP are resolved. Zhu et al [135] used polarisation and an RGBD stereo pair to disambiguate the polarisation surface normal estimates using a higher order graphical model.…”

Section: Combining Polarisation With Other Cuesmentioning

confidence: 99%

A Comprehensive Introduction to Photometric 3D-Reconstruction

Durou

Falcone

Quéau

et al. 2020

Advances in Computer Vision and Pattern Recognition

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Section: Combining Polarisation With Other Cuesmentioning

confidence: 99%

A Comprehensive Introduction to Photometric 3D-Reconstruction

Durou

Falcone

Quéau

et al. 2020

Advances in Computer Vision and Pattern Recognition

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“…Coarse geometry obtained by multi-view space carving [24], [25] has been used to resolve polarisation ambiguities. Kadambi et al [5], [26] combined a single polarisation image with a depth map obtained by an RGBD camera. The depth map is used to disambiguate the normals and provide a base surface for integration.…”

Section: Shape-from-polarisation and Shading A Polarisation Imagementioning

confidence: 99%

Height-from-Polarisation with Unknown Lighting or Albedo

Smith

Ramamoorthi

Tozza

2019

IEEE Trans. Pattern Anal. Mach. Intell.

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We present a method for estimating surface height directly from a single polarisation image simply by solving a large, sparse system of linear equations. To do so, we show how to express polarisation constraints as equations that are linear in the unknown height. The local ambiguity in the surface normal azimuth angle is resolved globally when the optimal surface height is reconstructed. Our method is applicable to dielectric objects exhibiting diffuse and specular reflectance, though lighting and albedo must be known. We relax this requirement by showing that either spatially varying albedo or illumination can be estimated from the polarisation image alone using nonlinear methods. In the case of illumination, the estimate can only be made up to a binary ambiguity which we show is a generalised Bas-relief transformation corresponding to the convex/concave ambiguity. We believe that our method is the first passive, monocular shape-from-x technique that enables well-posed height estimation with only a single, uncalibrated illumination condition. We present results on real world data, including in uncontrolled, outdoor illumination.

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“…Another intrinsic drawback of using shape from polarization is the ambiguous estimation of surface orientation. Previous developed solutions to disambiguate the surface normal often assume convexity on surface or require assistance from extra views or multi-wavelength 17,[22][23][24] . Smith et.…”

Section: Introductionmentioning

confidence: 99%

Computational Polarization 3D: new solution for monocular 3D imaging approach in natural conditions

Liu

Cai

Han

et al. 2021

Preprint

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Analyzing the polarimetric properties of the reflected light is a simple, fast, and low-cost approach to recover shape information, but no reported method can accurately recover surface shape from non-Lambertian object in natural conditions with a single view. Another major issue is the lack of effective method to address azimuth ambiguity during the surface reconstruction. To address these two major obstacles, we propose a monocular 3D polarization imaging approach for non-Lambertian surfaces by investigating the subtle difference in specular and diffuse reflection and then separating them using independent component analysis (ICA). Separated pure diffuse reflection enables accurate polarization extraction, based on which a gradient field is derived to determine surface normals. The ambiguity is removed by solving an optimization problem with a reference gradient field. We experimentally demonstrate the performance of the proposed method with man-made object under the controlled illumination and human face under natural illumination.

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Depth Sensing Using Geometrically Constrained Polarization Normals

Cited by 67 publications

References 57 publications

A Comprehensive Introduction to Photometric 3D-Reconstruction

A Comprehensive Introduction to Photometric 3D-Reconstruction

Height-from-Polarisation with Unknown Lighting or Albedo

Computational Polarization 3D: new solution for monocular 3D imaging approach in natural conditions

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