ACM SIGGRAPH 1994 Proceedings, 295-302.
Subdivision surfaces with sharp features, and their automatic creation by data fitting.
We present a general method for automatic reconstruction of accurate, concise, piecewise smooth surface
models from scattered range data. The method can be used in a variety of applications such as reverse
engineering — the automatic generation of CAD models from physical objects. Novel aspects of the
method are its ability to model surfaces of arbitrary topological type and to recover sharp features such
as creases and corners. The method has proven to be effective, as demonstrated by a number of examples
using both simulated and real data.
A key ingredient in the method, and a principal contribution of this paper, is the introduction of a new class of piecewise smooth surface representations based on subdivision. These surfaces have a number of properties that make them ideal for use in surface reconstruction: they are simple to implement, they can model sharp features concisely, and they can be fit to scattered range data using an unconstrained optimization procedure.
Hindsight: Through general optimization, this method is able to infer sharp features in the underlying geometry by simply fitting the data points. With the growing interest in subdivision surfaces, this surface fitting technique may prove useful. The paper is often cited for its introduction of sharp features in subdivision surface schemes. These features were extended in the work of Biermann et al. The SIGGRAPH 1998 paper by DeRose et al. presents extensions for "fractionally smooth" surface features.
ACM Copyright Notice
Copyright by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or firstname.lastname@example.org. The definitive version of this paper can be found at ACM's Digital Library http://www.acm.org/dl/.