| Abstract: | Consider the problem of constructing a mathematical representation of a curve that satisfies constraints such as interpolation of specified points. This problem arises frequently in the context of both data fitting and Computer Aided Design. We treat the most general problem: the curve may or may not be constrained to lie in a plane; the constraints may involve specified points, tangent vectors, normal vectors, and/or curvature vectors, periodicity, or nonlinear inequalities representing shapepreservation criteria. Rather than the usual piecewise parametric polynomial (B-spline) or rational (NURB) formulation, we represent the curve by a discrete sequence of vertices along with first, second, and third derivative vectors at each vertex, where derivatives are with respect to arc length. This provides third-order geometric continuity and maximizes flexibility with an arbitrarily large number of degrees of freedom. The free parameters are chosen to minimize a fairness measure defined as a weighted sum of curve length, total curvature, and variation of curvature. We thus obtain a very challenging constrained optimization problem for which standard methods are ineffective. A Sobolev gradient method, however, is particularly effective. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) |
