Variational surface modeling
W Welch, A Witkin - ACM SIGGRAPH computer graphics, 1992 - dl.acm.org
W Welch, A Witkin
ACM SIGGRAPH computer graphics, 1992•dl.acm.orgWe present a new approach to interactive modeling of freeform surfaces. Instead of a fixed
mesh of control points, the model presented to the user is that of an infinitely malleable
surface, with no fixed controls. The user is free to apply control points and curves which are
then available as handles for direct manipulation. The complexity of the surface's shape may
be increased by adding more control points and curves, without apparent limit. Within the
constraints imposed by the controls, the shape of the surface is fully determined by one or …
mesh of control points, the model presented to the user is that of an infinitely malleable
surface, with no fixed controls. The user is free to apply control points and curves which are
then available as handles for direct manipulation. The complexity of the surface's shape may
be increased by adding more control points and curves, without apparent limit. Within the
constraints imposed by the controls, the shape of the surface is fully determined by one or …
Abstract
We present a new approach to interactive modeling of freeform surfaces. Instead of a fixed mesh of control points, the model presented to the user is that of an infinitely malleable surface, with no fixed controls. The user is free to apply control points and curves which are then available as handles for direct manipulation. The complexity of the surface’s shape may be increased by adding more control points and curves, without apparent limit. Within the constraints imposed by the controls, the shape of the surface is fully determined by one or more simple criteria, such as smoothness. Our method for solving the resulting constrained variational optimization problems rests on a surface representation scheme allowing nonuniform subdivision of B-spline surfaces. Automatic subdivision is used to ensure that constraints are met, and to enforce error bounds. Efficient numerical solutions are obtained by exploiting linearities in the problem formulation and the representation.