A one‐dimensional homologically persistent skeleton of an unstructured point cloud in any metric space

@article{Kurlin2015AOH,
  title={A one‐dimensional homologically persistent skeleton of an unstructured point cloud in any metric space},
  author={V. Kurlin},
  journal={Computer Graphics Forum},
  year={2015},
  volume={34}
}
  • V. Kurlin
  • Published 2015
  • Mathematics, Computer Science
  • Computer Graphics Forum
  • Real data are often given as a noisy unstructured point cloud, which is hard to visualize. The important problem is to represent topological structures hidden in a cloud by using skeletons with cycles. All past skeletonization methods require extra parameters such as a scale or a noise bound. We define a homologically persistent skeleton, which depends only on a cloud of points and contains optimal subgraphs representing 1‐dimensional cycles in the cloud across all scales. The full skeleton is… CONTINUE READING
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