A kernel approach to gamut boundary computation

We present a kernel based method to associate an image gamut given as a point cloud in three-dimensional Euclidean space with a continuous shape. The shape we compute is implicitly given as the zero-set of a smooth function that we compute from the point cloud using an efficient optimization method. The feasibility of our approach is demonstrated on a couple of examples.