Skeletonisation algorithms with theoretical guarantees for unorganised point clouds with high levels of noise
作者：
Highlights：
• The paper evaluates algorithms that approximate unorganised point clouds by skeletons.
• A Homologically Persistent Skeleton (HoPeS) has guarantees proved for the first time.
• The optimality guarantee means that subgraphs of HoPeS show cycles hidden in a cloud.
• Other guarantees give conditions when a graph can be reconstructed from a noisy sample.
• Evaluations on large data show highest levels of noise for correct reconstructions.
摘要
•The paper evaluates algorithms that approximate unorganised point clouds by skeletons.•A Homologically Persistent Skeleton (HoPeS) has guarantees proved for the first time.•The optimality guarantee means that subgraphs of HoPeS show cycles hidden in a cloud.•Other guarantees give conditions when a graph can be reconstructed from a noisy sample.•Evaluations on large data show highest levels of noise for correct reconstructions.
论文关键词：Data skeletonisation,Noisy point sample,Persistent homology
论文评审过程：Received 24 June 2019, Revised 1 February 2021, Accepted 11 February 2021, Available online 20 February 2021, Version of Record 5 March 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.107902
