Polarization-Based Material Classification from Specular Reflection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A physical approach to color image understanding
International Journal of Computer Vision
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining Reflectance Properties of an Object Using Range and Brightness Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Separation of Reflection Components Using Color and Polarization
International Journal of Computer Vision
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Object shape and reflectance modeling from observation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
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International Journal of Computer Vision
A reflectance model for computer graphics
SIGGRAPH '81 Proceedings of the 8th annual conference on Computer graphics and interactive techniques
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting layers and analyzing their specular properties using epipolar-plane-image analysis
Computer Vision and Image Understanding
Specular Flow and the Recovery of Surface Structure
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Retrieving multiple light sources in the presence of specular reflections and texture
Computer Vision and Image Understanding
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Separation of reflection and transparency using epipolar plane image analysis
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Spectral imaging technique for visualizing the invisible information
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Spectral estimation of skin color with foundation makeup
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
A geometrical method of diffuse and specular image components separation
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
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A new method is described to estimate diffuse and specular reflectance parameters using spectral images, which overcomes the dynamic range limitation of imaging devices. After eliminating the influences of illumination and camera on spectral images, reflection values are initially assumed as diffuse-only reflection components, and subjected to the least squares method to estimate diffuse reflectance parameters at each wavelength on each single surface particle. Based on the dichromatic reflection model, specular reflection components are obtained, and then subjected to the least squares method to estimate specular reflectance parameters for gloss intensity and surface roughness. Experiments were carried out using both simulation data and measured spectral images. Our results demonstrate that this method is capable of estimating diffuse and specular reflectance parameters precisely for color and gloss reproduction, without requiring preprocesses such as image segmentation and synthesis of high dynamic range images.