Partitioning range images using curvature and scale

A method is presented for partitioning a set of surface estimates obtained with a laser range finding system into subsets corresponding to parts of an object. The authors´ strategy uses two complementary representations for surfaces, i.e., one which describes local structures in terms of differential properties (e.g., edges, lines, contours) and another which represents the surface as a collection of smooth patches at different scales. By enforcing a consistent interpretation between these two representations, it is possible to derive a partitioning algorithm that is both efficient and robust