Discrete & Computational Geometry

, Volume 51, Issue 1, pp 221–267 | Cite as

Manifold Reconstruction Using Tangential Delaunay Complexes



We give a provably correct algorithm to reconstruct a k-dimensional smooth manifold embedded in d-dimensional Euclidean space. The input to our algorithm is a point sample coming from an unknown manifold. Our approach is based on two main ideas: the notion of tangential Delaunay complex defined in Boissonnat and Flötotto (Comput. Aided Des. 36:161–174, 2004), Flötotto (A coordinate system associated to a point cloud issued from a manifold: definition, properties and applications. Ph.D. thesis, 2003), Freedman (IEEE Trans. Pattern Anal. Mach. Intell. 24(10), 2002), and the technique of sliver removal by weighting the sample points (Cheng et al. in J. ACM 47:883–904, 2000). Differently from previous methods, we do not construct any subdivision of the d-dimensional ambient space. As a result, the running time of our algorithm depends only linearly on the extrinsic dimension d while it depends quadratically on the size of the input sample, and exponentially on the intrinsic dimension k. To the best of our knowledge, this is the first certified algorithm for manifold reconstruction whose complexity depends linearly on the ambient dimension. We also prove that for a dense enough sample the output of our algorithm is isotopic to the manifold and a close geometric approximation of the manifold.


Tangential Delaunay complex Weighted Delaunay triangulation Manifold reconstruction Manifold learning Sampling conditions Sliver exudation 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.GeometricaINRIASophia-AntipolisFrance
  2. 2.ACM UnitIndian Statistical InstituteKolkataIndia

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