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I have some background in 2D computational geometry and understand how to find a convex hull in 2D. Now I'm looking at a set of vectors with 20-some components and want to find the convex hull on them.

I'm looking for an algorithm or even some kind of equivalence which would allow me to compute the convex boundaries of the set. I'm a bit out of my depth, so any insight would likely be valuable.

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What aspect are you trying to improve relative to these algorithms? – joriki Dec 14 '11 at 21:36
I know wikipedia claims that those algorithms are explained in higher dimesions, but I read through the lecture notes and didn't see any dimensions higher than 3. – codekaizen Dec 14 '11 at 22:11
The four algorithms described on the first page the article links to generalize to higher dimensions. The generalizations for Gift Wrap and Divide & Conquer are perhaps not obvious, but the ones for Incremental and Quick Hull are rather straightforward; they're spelled out in this lecture. – joriki Dec 14 '11 at 22:29

All I can - is to propose my own implementation of the Quickhull Algorithm written on C++. It works for any dimensionality and can be used for user-defined floating-point types.

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