2013 | OriginalPaper | Buchkapitel
Approximate Čech Complex in Low and High Dimensions
verfasst von : Michael Kerber, R. Sharathkumar
Erschienen in: Algorithms and Computation
Verlag: Springer Berlin Heidelberg
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Čech complexes reveal valuable topological information about point sets at a certain scale in arbitrary dimensions, but the sheer size of these complexes limits their practical impact. While recent work introduced approximation techniques for filtrations of (Vietoris-)Rips complexes, a coarser version of Čech complexes, we propose the approximation of Čech filtrations directly.
For fixed dimensional point set
S
, we present an approximation of the Čech filtration of
S
by a sequence of complexes of size linear in the number of points. We generalize well-separated pair decompositions (WSPD) to well-separated simplicial decomposition (WSSD) in which every simplex defined on
S
is covered by some element of WSSD. We give an efficient algorithm to compute a linear-sized WSSD in fixed dimensional spaces. Using a WSSD, we then present a linear-sized approximation of the filtration of Čech complex of
S
.
We also present a generalization of the known fact that the Rips complex approximates the Čech complex by a factor of
$\sqrt{2}$
. We define a class of complexes that interpolate between Čech and Rips complexes and that, given any parameter
ε
> 0, approximate the Čech complex by a factor (1 +
ε
). Our complex can be represented by
O
(
n
⌈1/2
ε
⌉
) simplices, up to purely combinatorial operations, without any hidden dependence on the ambient dimension of the point set. Our results are based on an interesting link between Čech complex and coresets for minimum enclosing ball of high-dimensional point sets. As a consequence of our analysis, we show improved bounds on coresets that approximate the radius of the minimum enclosing ball.