Recognition of shiny dielectric objects by analysing the polarization of reflected light
Image and Vision Computing
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Model Retrieval with Spherical Harmonics and Moments
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
Transparent Surface Modeling from a Pair of Polarization Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A surface-based approach for classification of 3D neuroanatomic structures
Intelligent Data Analysis
Two-dimensional BRDF estimation from polarisation
Computer Vision and Image Understanding
Polarization vision: a new sensory approach to image understanding
Image and Vision Computing
Recovery of surface orientation from diffuse polarization
IEEE Transactions on Image Processing
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This paper describes the use of polarisation information for surface segmentation based on material characteristics. We work with both polarised and unpolarised light, and hence domains where the polarisation is either specular or diffuse. We commence by using moments to estimate the components of the polarisation image (mean-intensity, polarisation degree and phase) from images obtained through multiple polariser orientations. From the Fresnel theory, the phase of light remitted from a surface is equal to the azimuth angle of the remitted direction, and for materials with restricted ranges of refractive index the polarisation degree determines the zenith angle. Based on this observation, we parameterise the angular distribution of the mean intensity for remitted light using spherical harmonics. We explore how vectors of spherical harmonics can be used to characterise varying surface reflectance distributions, and segment a scene into different material patches usingMahalanobis distances and normalized graph cuts.