Shape Analysis

Shape Analysis is a subfield of computer vision and machine vision that develops mathematical and algorithmic methods for representing, describing, and quantitatively comparing the geometric and topological properties of object shapes in images or spatial data, typically in a manner invariant to transformations such as translation, rotation, and scaling and supporting tasks such as recognition, segmentation, and shape grammar–based modeling.

16.2K

Publications

1.2M

Citations

30.9K

Authors

5.1K

Institutions

Publications per year

2017–2026

2.7K

Authors

30.9K

  1. LG
    Leonidas Guibas

    Stanford University, United States

    76 publications · 14.1K citations

    49

    h-index

  2. MM
    Michael M. Bronstein

    Università della Svizzera italiana, Switzerland

    65 publications · 8K citations

    40

    h-index

  3. TC
    T.F. Cootes

    University of Manchester, United Kingdom

    63 publications · 19.4K citations

    39

    h-index

  4. DC
    Daniel Cohen‐Or

    Tel Aviv University, Israel

    55 publications · 7.2K citations

    38

    h-index

  5. CT
    Chris Taylor

    University of Manchester, United Kingdom

    60 publications · 17.3K citations

    37

    h-index

1–5 of 30.9K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 740 publications · 202.2K citations

    173

    h-index

  2. Pattern Recognition

    444 publications · 33.1K citations

    86

    h-index

  3. ACM Transactions on Graphics

    TOG · 180 publications · 27.8K citations

    84

    h-index

  4. IEEE Transactions on Medical Imaging

    192 publications · 22.3K citations

    81

    h-index

  5. IEEE Transactions on Image Processing

    312 publications · 35.6K citations

    80

    h-index

1–5