The first, simplest, technique is to estimate the least-squares best approximating lumisphere for each surface point individually. Because the data lumisphere does not cover the entire sphere we need a roughness penalty to regularize the problem. We define our error functional as the the sum of a distance term which measures how well the lumisphere approximates the data lumisphere and a thin-plate energy term measuring the smoothness of the lumisphere.