Tozza, Silvia, Smith, William Alfred Peter orcid.org/0000-0002-6047-0413, Zhu, Dizhong et al. (2 more authors) (Accepted: 2017) Linear Differential Constraints for Photo-polarimetric Height Estimation. In: 2017 IEEE International Conference on Computer Vision (ICCV). IEEE Computer Society (In Press)
Abstract
In this paper we present a differential approach to photopolarimetric shape estimation. We propose several alternative differential constraints based on polarisation and photometric shading information and show how to express them in a unified partial differential system. Our method uses the image ratios technique to combine shading and polarisation information in order to directly reconstruct surface height, without first computing surface normal vectors. Moreover, we are able to remove the non-linearities so that the problem reduces to solving a linear differential problem. We also introduce a new method for estimating a polarisation image from multichannel data and, finally, we show it is possible to estimate the illumination directions in a two source setup, extending the method into an uncalibrated scenario. From a numerical point of view, we use a least-squares formulation of the discrete version of the problem. To the best of our knowledge, this is the first work to consider a unified differential approach to solve photo-polarimetric shape estimation directly for height. Numerical results on synthetic and real-world data confirm the effectiveness of our proposed method.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/N028481/1 |
Depositing User: | Pure (York) |
Date Deposited: | 02 Aug 2017 08:30 |
Last Modified: | 16 Oct 2024 10:53 |
Status: | In Press |
Publisher: | IEEE Computer Society |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119712 |
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