Convex layers

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The convex layers of a point set and their intersection with a halfplane Convex layers halfspace.svg
The convex layers of a point set and their intersection with a halfplane

In computational geometry, the convex layers of a set of points in the Euclidean plane are a sequence of nested convex polygons having the points as their vertices. The outermost one is the convex hull of the points and the rest are formed in the same way recursively. The innermost layer may be degenerate, consisting only of one or two points. [1] The problem of constructing convex layers has also been called onion peeling or onion decomposition. [2]

Although constructing the convex layers by repeatedly finding convex hulls would be slower, it is possible to partition any set of points into its convex layers in time . [1]

An early application of the convex layers was in robust statistics, as a way of identifying outliers and measuring the central tendency of a set of sample points. [3] [4] In this context, the number of convex layers surrounding a given point is called its convex hull peeling depth, and the convex layers themselves are the depth contours for this notion of data depth. [5]

Convex layers may be used as part of an efficient range reporting data structure for listing all of the points in a query half-plane. The points in the half-plane from each successive layer may be found by a binary search to find the most extreme point in the direction of the half-plane, and then searching sequentially from there. Fractional cascading can be used to speed up the binary searches, giving total query time to find points out of a set of . [6]

The points of an grid have convex layers, [7] as do the same number of uniformly random points within any convex shape. [8]

Related Research Articles

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<span class="mw-page-title-main">Heilbronn triangle problem</span> On point sets with no small-area triangles

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<span class="mw-page-title-main">Simple polygon</span> Shape bounded by non-intersecting line segments

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<span class="mw-page-title-main">Point-set triangulation</span>

A triangulation of a set of points in the Euclidean space is a simplicial complex that covers the convex hull of , and whose vertices belong to . In the plane, triangulations are made up of triangles, together with their edges and vertices. Some authors require that all the points of are vertices of its triangulations. In this case, a triangulation of a set of points in the plane can alternatively be defined as a maximal set of non-crossing edges between points of . In the plane, triangulations are special cases of planar straight-line graphs.

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In computer science, a k-d tree is a space-partitioning data structure for organizing points in a k-dimensional space. k-d trees are a useful data structure for several applications, such as searches involving a multidimensional search key and creating point clouds. k-d trees are a special case of binary space partitioning trees.

In graph theory and computer science, the lowest common ancestor (LCA) of two nodes v and w in a tree or directed acyclic graph (DAG) T is the lowest node that has both v and w as descendants, where we define each node to be a descendant of itself.

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In computer science, the range searching problem consists of processing a set S of objects, in order to determine which objects from S intersect with a query object, called the range. For example, if S is a set of points corresponding to the coordinates of several cities, find the subset of cities within a given range of latitudes and longitudes.

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In computational geometry, the Bentley–Ottmann algorithm is a sweep line algorithm for listing all crossings in a set of line segments, i.e. it finds the intersection points of line segments. It extends the Shamos–Hoey algorithm, a similar previous algorithm for testing whether or not a set of line segments has any crossings. For an input consisting of line segments with crossings, the Bentley–Ottmann algorithm takes time . In cases where , this is an improvement on a naïve algorithm that tests every pair of segments, which takes .

<span class="mw-page-title-main">Kenneth L. Clarkson</span> American computer scientist

Kenneth Lee Clarkson is an American computer scientist known for his research in computational geometry. He is a researcher at the IBM Almaden Research Center, and co-editor-in-chief of the Journal of Computational Geometry.

In computational geometry, a CC system or counterclockwise system is a ternary relation pqr introduced by Donald Knuth to model the clockwise ordering of triples of points in general position in the Euclidean plane.

<span class="mw-page-title-main">Maxima of a point set</span>

In computational geometry, a point p in a finite set of points S is said to be maximal or non-dominated if there is no other point q in S whose coordinates are all greater than or equal to the corresponding coordinates of p. The maxima of a point setS are all the maximal points of S. The problem of finding all maximal points, sometimes called the problem of the maxima or maxima set problem, has been studied as a variant of the convex hull and orthogonal convex hull problems. It is equivalent to finding the Pareto frontier of a collection of points, and was called the floating-currency problem by Herbert Freeman based on an application involving comparing the relative wealth of individuals with different holdings of multiple currencies.

<span class="mw-page-title-main">Relative convex hull</span>

In discrete geometry and computational geometry, the relative convex hull or geodesic convex hull is an analogue of the convex hull for the points inside a simple polygon or a rectifiable simple closed curve.

References

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