Robot vision
Surface Identification Using the Dichromatic Reflection Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Illumination for computer generated pictures
Communications of the ACM
Models of light reflection for computer synthesized pictures
SIGGRAPH '77 Proceedings of the 4th annual conference on Computer graphics and interactive techniques
A reflectance model for computer graphics
SIGGRAPH '81 Proceedings of the 8th annual conference on Computer graphics and interactive techniques
Parameter Estimation of a Reflection Model from a Multi-band Image
PMCVG '99 Proceedings of the 1999 IEEE Workshop on Photometric Modeling for Computer Vision and Graphics
A signal-processing framework for inverse rendering
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Refractive index estimation and color image rendering
Pattern Recognition Letters - Special issue: Colour image processing and analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mixture of Spherical Distributions for Single-View Relighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Correction of color information of a 3D model using a range intensity image
Computer Vision and Image Understanding
International Journal of Computer Vision
Computer Graphics Forum
An optimisation approach to the recovery of reflection parameters from a single hyperspectral image
Computer Vision and Image Understanding
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This article describes a method for estimating parameters of a reflection model from a single color image taken by a CCD camera. We used the Phong-type dichromatic reflection model for modeling light reflection on an object surface composed of nonconducting materials. We developed several algorithms for estimating model parameters and present experimental results using a real image of a plastic cylinder. Next, we generalized the approach to objects with general shapes. The feasibility of the generalization is demonstrated using both synthesized and real images.