Computing the alpha complex using dual active set quadratic programming

Abstract

AbstractThe alpha complex is a fundamental data structure from computational geometry, which encodes the topological type of a union of balls $$B(x;r) \subset {\mathbb {R}}^m$$ B ( x ; r ) ⊂ R m for $$x\in S$$ x ∈ S , including a weighted version that allows for varying radii. It consists of the collection of “simplices” $$\sigma =\{x_0,...,x_k\} \subset S$$ σ = { x 0 , . . . , x k } ⊂ S , which correspond to nonempty $$(k+1)$$ ( k + 1 ) -fold intersections of cells in a radius-restricted version of the Voronoi diagram $${{\,\textrm{Vor}\,}}(S,r)$$ Vor ( S , r ) . Existing algorithms for computing the alpha complex require that the points reside in low dimension because they begin by computing the entire Delaunay complex, which rapidly becomes intractable, even when the alpha complex is of a reasonable size. This paper presents a method for computing the alpha complex without computing the full Delaunay triangulation by applying Lagrangian duality, specifically an algorithm based on dual quadratic programming that seeks to rule simplices out rather than ruling them in.