3D surface reconstruction based on combined analysis of reflectance and polarisation properties

In this paper we present a novel image-based 3D surface reconstruction technique that incorporates both reflectance and polarisation features into a variational framework. The proposed technique is suitable for singleimage and multi-image (photopolarimetric stereo) analysis. It is especially suited for the difficult task of 3D reconstruction of rough metallic surfaces. An error functional consisting of several error terms related to the measured reflectance and polarisation properties is minimised in order to obtain a 3D reconstruction of the surface. We show that the combined approach strongly increases the accuracy of the surface reconstruction result, compared to techniques based on either reflectance or polarisation alone. We perform an evaluation of the algorithm with respect to single and multiple reflectance and polarisation images of the surface, relying on synthetic ground truth data. This evaluation also reveals which polarisation features should preferably be used in the context of 3D reconstruction of rough metallic surfaces. Furthermore, we report 3D reconstruction results for a raw forged iron surface, thus showing the applicability of our method in real-world scenarios, here in the domain of industrial quality inspection.