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|a 10.1109/TPAMI.2021.3078101
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|a eng
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|a Tozza, Silvia
|e verfasserin
|4 aut
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|a Uncalibrated, Two Source Photo-Polarimetric Stereo
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|c 2022
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|a Text
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|a ƒaComputermedien
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|a Date Revised 05.08.2022
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a In this paper we present methods for estimating shape from polarisation and shading information, i.e. photo-polarimetric shape estimation, under varying, but unknown, illumination, i.e. in an uncalibrated scenario. We propose several alternative photo-polarimetric constraints that depend upon the partial derivatives of the surface and show how to express them in a unified system of partial differential equations of which previous work is a special case. By careful combination and manipulation of the constraints, we show how to eliminate non-linearities such that a discrete version of the problem can be solved using linear least squares. We derive a minimal, combinatorial approach for two source illumination estimation which we use with RANSAC for robust light direction and intensity estimation. We also introduce a new method for estimating a polarisation image from multichannel data and provide methods for estimating albedo and refractive index. We evaluate lighting, shape, albedo and refractive index estimation methods on both synthetic and real-world data showing improvements over existing state-of-the-art
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|a Journal Article
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|a Zhu, Dizhong
|e verfasserin
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1 |
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|a Smith, William A P
|e verfasserin
|4 aut
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| 700 |
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|a Ramamoorthi, Ravi
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hancock, Edwin R
|e verfasserin
|4 aut
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|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 44(2022), 9 vom: 24. Sept., Seite 5747-5760
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|u http://dx.doi.org/10.1109/TPAMI.2021.3078101
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