A Note on Local Min-Max affine approximations of real-valued convex functions in R^k with applications to computer vision

We present a method to find local Min-Max affine approximants of convex functions f:R^k-R on a simplex in R^k. Our method finds an optimal affine approximant for the given f. We apply our result to an application in computer vision.