By the same authors

Linear Differential Constraints for Photo-polarimetric Height Estimation

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Title of host publication2017 IEEE International Conference on Computer Vision (ICCV)
DateAccepted/In press - 17 Jul 2017
Number of pages9
PublisherIEEE Computer Society Press
Original languageEnglish

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.

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