Shape from shading
Surface Reflection: Physical and Geometrical Perspectives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Height and Gradient from Shading
Height and Gradient from Shading
Polarization-based Inverse Rendering from a Single View
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Transparent Surface Modeling from a Pair of Polarization Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photometric Stereo Under Blurred Observations
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
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In this paper we present a novel image-based 3D surface reconstruction technique that incorporates reflectance, polarisation, and defocus information into a variational framework. Our technique is especially suited for the difficult task of 3D reconstruction of rough metallic surfaces. An error functional composed of several error terms related to the measured reflectance and polarisation properties is minimised by means of an iterative scheme in order to obtain a 3D reconstruction of the surface. This iterative algorithm is initialised with the result of depth from defocus analysis. By evaluating the algorithm on synthetic ground truth data, we show that the combined approach strongly improves the accuracy of the surface reconstruction result compared to techniques based on either reflectance or polarisation alone. Furthermore, we report 3D reconstruction results for a raw forged iron surface. A comparison of our method to independently measured ground truth data yields an accuracy of about one third of the pixel resolution.