Abstract: This paper is concerned with polarimetric dense map reconstruction based on a
polarization camera with the help of relative depth information as a prior. In
general, polarization imaging is able to reveal information about surface
normal such as azimuth and zenith angles, which can support the development of
solutions to the problem of dense reconstruction, especially in texture-poor
regions. However, polarimetric shape cues are ambiguous due to two types of
polarized reflection (specular/diffuse). Although methods have been proposed to
address this issue, they either are offline and therefore not practical in
robotics applications, or use incomplete polarimetric cues, leading to
sub-optimal performance. In this paper, we propose an online reconstruction
method that uses full polarimetric cues available from the polarization camera.
With our online method, we can propagate sparse depth values both along and
perpendicular to iso-depth contours. Through comprehensive experiments on
challenging image sequences, we demonstrate that our method is able to
significantly improve the accuracy of the depthmap as well as increase its
density, specially in regions of poor texture.