Recognition of shiny dielectric objects by analysing the polarization of reflected light
Image and Vision Computing
Polarization-Based Material Classification from Specular Reflection
IEEE Transactions on Pattern Analysis and Machine Intelligence
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 uses polarisation information for surface segmentation based on material reflectance characteristics. Both polarised and unpolarised light is used, and the method is hence applicable to both specular or diffuse polarisation. We use moments to estimate the mean-intensity, polarisation and phase from images obtained with multiple polariser orientations. From the Fresnel theory, the azimuth angle of the surface normal is determined by the phase angle and for a limited range of refractive index the zenith angle is determined by the degree of polarisation. Using these properties, we show how the angular distribution of the mean intensity for remitted light can be parameterised using spherical harmonics. We explore two applications of our technique, namely a) detecting skin lesions in damaged fruit, and b) exploiting spherical harmonic co-efficients to segment surfaces into regions of different material composition using normalized graph cuts.