How to Efficiently Triangulate a Concave Shape?

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To efficiently triangulate a closed concave shape, the goal is to minimize sliver triangles and ensure reasonable computation time for meshes with around 10,000 vertices. The Delaunay triangulation method is effective for convex shapes, but challenges arise when applied to concave shapes. A suggested approach involves forming the convex hull of the polygon and then applying Delaunay triangulation while avoiding crossing existing edges. After triangulation, any lines outside the original polygon should be removed. This method aims to balance computational efficiency with the quality of the resulting triangulation.
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I am looking for a "good" way to triangulate a closed concave shape of vertices and edges.

"good" is quite a vague term, but the basic principles I'm interested in are:
1) Minimize "sliver" triangles that are very thin and contain really small angles.
2) Must be reasonable to compute. Ideally it would take less than a day to compute the triangulization for a mesh with ~10,000 vertices on a standard computer (so complete brute force is out).

Here is a diagram (initial shape in black):
http://img394.imageshack.us/img394/3077/concavetriangle.png

If the mesh was convex, a good strategy would be http://en.wikipedia.org/wiki/Delaunay_trianglulation method could work well if I had a fast way of finding the worst possible triangle among a subset of the shape, but I'm having no luck there.
 
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Suggestion (it may not be very good): Form the convex hull of the polygon. Use Delaunay, being careful you don't cross any existing lines. Get rid of lines outside original polygon.
 
I think the Delaunay triangulization is unique
 
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