A Geometric Model for Polarization Imaging on Projective Cameras

• URL: http://arxiv.org/abs/2211.16986v1
• Date: Tue, 29 Nov 2022 17:12:26 GMT
• Title: A Geometric Model for Polarization Imaging on Projective Cameras
• Authors: Mara Pistellato and Filippo Bergamasco
• Abstract summary: We present a geometric model describing how a general projective camera captures the light polarization state. Our model is implemented as a pre-processing operation acting on raw images, followed by a per-pixel rotation of the reconstructed normal field. Experiments on existing and new datasets demonstrate the accuracy of the model when applied to commercially available polarimetric cameras.
• Score: 5.381004207943598
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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