Convex Hull Complexity

Convex Hull Complexity is a computational geometry metric that quantifies the minimal descriptive complexity required to represent the convex hull of a given point set in Euclidean space, distinguishing it by characterizing the intrinsic algorithmic and structural intricacy associated with the hull's shape, dimensionality, and vertex configuration.

61

Publications

4.4K

Citations

105

Authors

65

Institutions

Publications per year

2017–2026

2

Authors

105

  1. TM
    Timothy M. Chan

    University of Waterloo, Canada

    5 publications · 190 citations

    5

    h-index

  2. RS
    Raimund Seidel

    University of California, Berkeley, United States

    3 publications · 676 citations

    3

    h-index

  3. PL
    Peter L. Bartlett

    University of California, Berkeley, United States

    2 publications · 111 citations

    2

    h-index

  4. SO
    Stephan Olariu

    Old Dominion University, United States

    2 publications · 30 citations

    2

    h-index

  5. FP
    Franco P. Preparata

    University of Illinois Urbana-Champaign, United States

    2 publications · 43 citations

    2

    h-index

1–5 of 105

Venues

  1. SIAM Journal on Computing

    5 publications · 565 citations

    5

    h-index

  2. Information Processing Letters

    3 publications · 533 citations

    3

    h-index

  3. Computational Geometry

    3 publications · 301 citations

    3

    h-index

  4. 3

    h-index

  5. BIT Numerical Mathematics

    3 publications · 99 citations

    3

    h-index

1–5