For a given homogeneous region, the first
component of the prediction it makes about the image concerns its color.
In early work, I developed a novel way of defining an object’s color
by sampling pixels from it, fitting an ellipsoid to those pixels’ colorspace projection
using principal
components analysis, and quantifying color similarity by
the Mahalanobis distance, as you see here, where
brighter pixels are more orange.