A Geometric Model for Polarization Imaging on Projective Cameras
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 50 references that are in the map. First posted on arXiv 29 Nov 2022.
Builds on
5 of 50 references.
References · 5
- 2021Shape from Polarization for Complex Scenes in the Wildcited by 53
- 2020Polarimetric Multi-View Inverse Renderingcited by 28
- 2022Perspective Phase Angle Model for Polarimetric 3D Reconstructioncited by 11
- 2021Polarimetric Monocular Dense Mapping Using Relative Deep Depth Priorcited by 8
- 2016Shape from Mixed Polarizationcited by 3
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