Polarization-Based Material Classification from Specular Reflection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polarization methods in computer vision
Polarization methods in computer vision
Direct calibration and data consistency in 3-D laser scanning
BMVC 94 Proceedings of the conference on British machine vision (vol. 2)
A Reflectance Model for Computer Graphics
ACM Transactions on Graphics (TOG)
Improving Depth Image Acquisition Using Polarized Light
International Journal of Computer Vision
Robust Segmentation of Primitives from Range Data in the Presence of Geometric Degeneracy
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Estimation Using Polarization and Shading from Two Views
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fluorescent immersion range scanning
ACM SIGGRAPH 2008 papers
Analysis of directional reflectance and surface orientation using fresnel theory
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
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We use polarization analysis in triangulation-based laser scanning to disambiguate the true laser stripe from spurious inter-reflections caused by holes and concavities on metal surfaces. Stripe candidates are discriminated by projecting linearly polarized laser light onto the objects, and measuring the polarization state of the reflected light at each pixel of the various candidates. We sketch a model for predicting the polarization state of the true stripe, and report several experimental results.