In this talk, I address a new take on adaptive sampling with respect to the local feature size, i.e., the distance to the medial axis. We recently proved that such samples can be viewed as uniform samples with respect to an alternative metric on the Euclidean space. The idea of adaptive metrics gives a general way to adapt the critical point theory of distance functions to locally adaptive sampling conditions.