@conference {781,
title = {Estimating the tensor of curvature of a surface from a polyhedral approximation},
year = {1995},
pages = {902-902},
publisher = {IEEE Computer Society},
organization = {IEEE Computer Society},
abstract = {Estimating principal curvatures and principal directions of a surface from a polyhedral approximation with a large number of small faces, such as those produced by iso-surface construction algorithms, has become a basic step in many computer vision algorithms, particularly in those targeted at medical applications. We describe a method to estimate the tensor of curvature of a surface at the vertices of a polyhedral approximation. Principal curvatures and principal directions are obtained by computing in closed form the eigenvalues and eigenvectors of certain 3/spl times/3 symmetric matrices defined by integral formulas, and closely related to the matrix representation of the tensor of curvature. The resulting algorithm is linear, both in time and in space, as a function of the number of vertices and faces of the polyhedral surface.},
keywords = {computational geometry computer vision eigenvalues eigenvalues and eigenfunctions eigenvectors integral formulas iso-surface construction algorithms matrix representation medical applications polyhedral approximation polyhedral surface principal curvature},
author = {Gabriel Taubin}
}