Skeleton-based Representation

Skeleton-Based Representation is a shape representation method that captures the intrinsic topology and geometry of a shape through a 1D medial axis or skeletal structure, distinguished from boundary-based or volumetric representations by its emphasis on hierarchical connectivity and part abstraction.

629

Publications

49.5K

Citations

1.8K

Authors

637

Institutions

Publications per year

2017–2026

237

Variants

Medial Axis Representation

Authors

1.8K

  1. GS
    Gabriella Sanniti di Baja

    Istituto di Cibernetica “Eduardo Caianiello”, Italy

    14 publications · 1.2K citations

    12

    h-index

  2. AT
    Alexandru Telea

    University of Groningen, Netherlands

    9 publications · 543 citations

    9

    h-index

  3. XB
    Xiang Bai

    Huazhong University of Science and Technology, China

    7 publications · 342 citations

    7

    h-index

  4. WL
    Wenyu Liu

    Huazhong University of Science and Technology, China

    6 publications · 284 citations

    6

    h-index

  5. SS
    Stina Svensson

    Swedish University of Agricultural Sciences, Sweden

    6 publications · 199 citations

    6

    h-index

1–5 of 1.8K

Venues

  1. Pattern Recognition

    26 publications · 2.6K citations

    22

    h-index

  2. 19

    h-index

  3. Pattern Recognition Letters

    23 publications · 1.1K citations

    17

    h-index

  4. Computer Vision and Image Understanding

    CVIU · 15 publications · 1.6K citations

    14

    h-index

  5. Computer Graphics Forum

    13 publications · 856 citations

    12

    h-index

1–5