Polarization-based inverse rendering from a single view

Miyazaki,; Tan, Daoyong; Hara,; Ikeuchi,

doi:10.1109/iccv.2003.1238455

Cited by 154 publications

(104 citation statements)

References 25 publications

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“…To remedy the ill-posedness nature of the problem, Miyazaki et al [27] has assumed that the histogram of zenith angles for a given object was similar to that for a sphere. He has used this property to recover a mapping from the degree of polarisation to the zenith angle.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the mapping is not necessarily consistent across different material refractive indices. The related work in [27] and [26] employed the degree of polarisation in the visible and far-infrared regions to resolve ambiguities in determining the surface orientation of transparent objects. The main drawback of the method in [26] is the need for an omni-directional diffuse illumination source, which limits its applicability in real-world settings.…”

Section: Introductionmentioning

confidence: 99%

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Shape and Refractive Index from Single-View Spectro-Polarimetric Images

2012

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In this paper, we address the problem of the simultaneous recovery of the shape and refractive index of an object from a spectro-polarimetric image captured from a single view. Here, we focus on the diffuse polarisation process occuring at dielectric surfaces due to subsurface scattering and transmission from the object surface into the air. The diffuse polarisation of the reflection process is modelled by the Fresnel transmission theory. We present a method for estimating the azimuth angle of surface normals from the spectral variation of the phase of polarisation. Moreover, we estimate the zenith angle of surface normals and index of refraction simultaneously in a well-posed optimisation framework. We achieve well-posedness by introducing two additional constraints to the problem, including the surface integrability and the material dispersion equation. This yields an iterative solution which is computationally efficient due to the use of closed-form solutions for both the zenith angle and the refractive index in each iteration. To demonstrate the effectiveness of our approach, we show results of shape recovery and surface rendering for both real-world and synthetic imagery.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Shape and Refractive Index from Single-View Spectro-Polarimetric Images

2012

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“…This is not exclusive to our method but rather common across other reflectance parameter estimation approaches [13,31]. Specularity removal is often used to decompose the image radiance into specular and diffuse reflection.…”

Section: Optimisation Proceduresmentioning

confidence: 99%

An optimisation approach to the recovery of reflection parameters from a single hyperspectral image

Rahman

Robles-Kelly

2013

Computer Vision and Image Understanding

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In this paper, we present a method to recover the parameters governing the reflection of light from a surface making use of a single hyperspectral image. To do this, we view the image radiance as a combination of specular and diffuse reflection components and present a cost functional which can be used for purposes of iterative least squares optimisation. This optimisation process is quite general in nature and can be applied to a number of reflectance models widely used in the computer vision and graphics communities. We elaborate on the use of these models in our optimisation process and provide a variant of the Beckmann-Kirchhoff model which incorporates the Fresnel reflection term. We show results on synthetic images and illustrate how the recovered photometric parameters can be employed for skin recognition in real world imagery, where our estimated albedo yields a classification rate of 95.09 ± 4.26% as compared to an alternative, whose classification rate is of 90.94 ± 6.12%. We also show quantitative results on the estimation of the index of refraction, where our method delivers an average per-pixel angular error of 0.15 degrees. This is a considerable improvement with respect to an alternative, which yields an error of 9.9 degrees.

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“…We can also further imposes smoothing constraint to the resulted azimuths α and zeniths ζ (see [15]). …”

Section: Reference Points Selectionmentioning

confidence: 99%

A Combinatorial Transparent Surface Modeling from Polarization Images

Fanany

Kobayashi

Kumazawa

2004

Lecture Notes in Computer Science

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Abstract. This paper presents a combinatorial (decision tree induction) technique for transparent surface modeling from polarization images. This technique simultaneously uses the object's symmetry, brewster angle, and degree of polarization to select accurate reference points. The reference points contain information about surface's normals position and direction at near occluding boundary. We reconstruct rotationally symmetric objects by rotating these reference points.

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Polarization-based inverse rendering from a single view

Abstract: Abstract

Cited by 154 publications

References 25 publications

Shape and Refractive Index from Single-View Spectro-Polarimetric Images

Shape and Refractive Index from Single-View Spectro-Polarimetric Images

An optimisation approach to the recovery of reflection parameters from a single hyperspectral image

A Combinatorial Transparent Surface Modeling from Polarization Images

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