Dimension detection via slivers

Siu Wing Cheng*, Man Kwun Chiu

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

12 Citations (Scopus)

Abstract

We present a novel approach to estimate the dimension m of an unknown manifold M ⊂ ℝd with positive reach from a set of point samples P ⊂ M. It works by analyzing the shape of simplices formed by point samples. Suppose that P is drawn from M according to a Poisson process with an unknown parameter λ. Let k be some fixed positive integer. When λ is large enough, we prove that the dimension can be correctly output in O(kd|P|1+1/k) time with probability greater than 1 - 2-k. We experimented with a practical variant and showed that its performance is competitive with several previous methods.

Original languageEnglish
Title of host publicationProceedings of the 20th Annual ACM-SIAM Symposium on Discrete Algorithms
PublisherAssociation for Computing Machinery (ACM)
Pages1001-1010
Number of pages10
ISBN (Print)9780898716801
DOIs
Publication statusPublished - 2009
Event20th Annual ACM-SIAM Symposium on Discrete Algorithms - New York, NY, United States
Duration: 4 Jan 20096 Jan 2009

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

Conference

Conference20th Annual ACM-SIAM Symposium on Discrete Algorithms
Country/TerritoryUnited States
CityNew York, NY
Period4/01/096/01/09

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