A Geometric Model for Polarization Imaging on Projective Cameras

TL;DR

This paper introduces a geometric model that accurately describes how projective cameras capture polarization information, enabling existing Shape-from-Polarization methods to be adapted for real-world, perspective imaging scenarios.

Contribution

The paper presents a novel geometric model for polarization imaging with projective cameras, bridging the gap between idealized orthographic assumptions and real-world perspective cameras.

Findings

Model aligns with state-of-the-art renderers

Enforces physical constraints among channels

Improves accuracy on commercial polarimetric cameras

Abstract

The vast majority of Shape-from-Polarization (SfP) methods work under the oversimplified assumption of using orthographic cameras. Indeed, it is still not well understood how to project the Stokes vectors when the incoming rays are not orthogonal to the image plane. We try to answer this question presenting a geometric model describing how a general projective camera captures the light polarization state. Based on the optical properties of a tilted polarizer, our model is implemented as a pre-processing operation acting on raw images, followed by a per-pixel rotation of the reconstructed normal field. In this way, all the existing SfP methods assuming orthographic cameras can behave like they were designed for projective ones. Moreover, our model is consistent with state-of-the-art forward and inverse renderers (like Mitsuba3 and ART), intrinsically enforces physical constraints among the captured channels, and handles demosaicing of DoFP sensors. Experiments on existing and new datasets demonstrate the accuracy of the model when applied to commercially available polarimetric cameras.