BlumNet: Graph Component Detection for Object Skeleton Extraction

Yulu Zhang, Liang Sang, Marcin Grzegorzek, John See, Cong Yang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper, we present a simple yet efficient framework, BlumNet, for extracting object skeletons in natural images and binary shapes. With the need for highly reliable skeletons in various multimedia applications, the proposed BlumNet is distinguished in three aspects: (1) The inception of graph decomposition and reconstruction strategies further simplifies the skeleton extraction task into a graph component detection problem, which significantly improves the accuracy and robustness of extracted skeletons. (2) The intuitive representation of each skeleton branch with multiple structured and overlapping line segments can effectively prevent the skeleton branch vanishing problem. (3) In comparison to traditional skeleton heatmaps, our approach directly outputs skeleton graphs, which is more feasible for real-world applications. Through comprehensive experiments, we demonstrate the advantages of BlumNet: significantly higher accuracy than the state-of-the-art AdaLSN (0.826 vs. 0.786) on the SK1491 dataset, a marked improvement in robustness on mixed object deformations, and also a state-of-the-art performance on binary shape datasets (e.g. 0.893 on the MPEG7 dataset).

Original languageEnglish
Title of host publicationMM '22: Proceedings of the 30th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450392037
Publication statusPublished - 10 Oct 2022
Event30th ACM International Conference on Multimedia 2022 - Lisbon, Portugal
Duration: 10 Oct 202214 Oct 2022


Conference30th ACM International Conference on Multimedia 2022
Abbreviated titleMM 2022


  • skeleton
  • skeleton extraction
  • skeleton graph
  • transformer

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software


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