Progressive simplicial complexes
ACM SIGGRAPH 1997 Proceedings, 217-224.
Progressive encoding of both topology and geometry.
In this paper, we introduce the progressive simplicial complex (PSC) representation, a new format for
storing and transmitting triangulated geometric models. Like the earlier progressive mesh (PM)
representation, it captures a given model as a coarse base model together with a sequence of refinement
transformations that progressively recover detail. The PSC representation makes use of a more general
refinement transformation, allowing the given model to be an arbitrary triangulation (e.g. any dimension,
non-orientable, non-manifold, non-regular), and the base model to always consist of a single vertex.
Indeed, the sequence of refinement transformations encodes both the geometry and the topology of the model
in a unified multiresolution framework. The PSC representation retains the advantages of PM's. It defines
a continuous sequence of approximating models for runtime level-of-detail control, allows smooth
transitions between any pair of models in the sequence, supports progressive transmission, and offers a
space-efficient representation. Moreover, by allowing changes to topology, the PSC sequence of
approximations achieves better fidelity than the corresponding PM sequence.
We develop an
optimization algorithm for constructing PSC representations for graphics surface models, and demonstrate
the framework on models that are both geometrically and topologically complex.
It is an elegant framework for progressively encoding topology, although perhaps overly general for
Solutions have since been developed for the case of progressive tetrahedralizations, another interesting
generalization of progressive meshes.
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/.