Perspective Phase Angle Model for Polarimetric 3D Reconstruction
This work addresses a domain-specific problem for computer vision researchers and practitioners in 3D reconstruction, offering an incremental improvement by extending existing models to perspective cameras.
The paper tackles the problem of polarimetric 3D reconstruction under perspective projection, which current methods assume orthographic projection, leading to errors in large fields of view. The proposed perspective phase angle model improves accuracy for surface normal estimation from single-view phase angle maps, as shown in experiments on real data.
Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption. In the case of a large field of view, however, this assumption does not hold and may result in significant reconstruction errors in methods that make this assumption. To address this problem, we present the perspective phase angle (PPA) model that is applicable to perspective cameras. Compared with the orthographic model, the proposed PPA model accurately describes the relationship between polarization phase angle and surface normal under perspective projection. In addition, the PPA model makes it possible to estimate surface normals from only one single-view phase angle map and does not suffer from the so-called $π$-ambiguity problem. Experiments on real data show that the PPA model is more accurate for surface normal estimation with a perspective camera than the orthographic model.