User:Cdecoro/Mesh Simplification

Mesh simplification (also mesh decimation) is the subfield of computer graphics research that studies the approximation of a complex, high-resolution polygonal mesh with simpler geometry that resembles the original, but with fewer geometric primitives. This is used especially with geometry acquired from real-world sources, such as laser-triangulation or photometric stereo, as the resulting models tend to have significant resolution, much of which is overtessellated.

Note that this particular field deals specifically with the use of polygonal (frequently triangular) meshes as boundary representations of geometric objects, and their approximation at lower resolution. This definition excludes methods that approximate geometry with other types of boundary representations (NURBS and subdivision surfaces are commonly used examples) or with non-boundary (volumetric or point-sampled) representations. While significant work exists in these areas, they are generally considered distinct fields.

Methods of decimation can be broadly classified into two types. Clustering methods identify a subsets of the original geometry that can be replaced with a smaller number of representative primitives in the output; an example is the replacement of all vertices in a fixed subdivision of space with a single vertex. Iterative decimation methods define a particular primitive decimation operation, such as the collapse of the two vertices of an edge into a single vertex, and the subsequent removal of resulting degenerate triangles. This primitive operation is applied repeatedly, in an order specified by a given decimation metric, until the desired resolution is reached.

Variations of Mesh Simplification
The problem of mesh simplification, as originally posed, required a single static (non-deforming) mesh to be approximated by another static mesh; further, neither the vantage point of the viewer, nor non-geometric properties of the object (such as color) were to be taken into consideration when performing simplification. Later work has addressed many of these variations on the original problem.