What is the Spectral Dimensionality of Illumination Functions in Outdoor Scenes?
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Estimation of illumination characteristics
IEEE Transactions on Image Processing
Two stage principal component analysis of color
IEEE Transactions on Image Processing
Lie methods for color robot vision
Robotica
Coloring Action Recognition in Still Images
International Journal of Computer Vision
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It is known that for every selection of illumination spectra there is a coordinate system such that all coordinate vectors of these illumination spectra are located in a cone. A natural set of transformations of this cone are the Lorentz transformations. In this paper we investigate if sequences of illumination spectra can be described by one-parameter subgroups of Lorentz-transformations. We present two methods to estimate the parameters of such a curve from a set of coordinate points. We also use an optimization technique to approximate a given set of points by a one-parameter curve with a minimum approximation error. In the experimental part of the paper we investigate series of blackbody radiators and sequences of measured daylight spectra and show that one-parameter curves provide good approximations for large sequences of illumination spectra.