Error-bounded Simplification

Error-Bounded Simplification is a geometric simplification technique that reduces the complexity of a model while guaranteeing that the deviation between the original and simplified representation remains within a specified tolerance threshold.

15

Publications

611

Citations

44

Authors

25

Institutions

Publications per year

2017–2026

5

Authors

44

  1. MG
    Michael Garland

    University of Illinois Urbana-Champaign, United States

    2 publications · 149 citations

    2

    h-index

  2. MV
    Marc van Kreveld

    Utrecht University, Netherlands

    2 publications · 76 citations

    2

    h-index

  3. BW
    Bin Wang

    Tsinghua University, China

    1 publications · 21 citations

    1

    h-index

  4. TW
    Tianyu Wo

    Beihang University, China

    1 publications · 28 citations

    1

    h-index

  5. JJ
    Jiahao Jiang

    Shanghai Jiao Tong University, China

    1 publications · 28 citations

    1

    h-index

1–5 of 44

Venues

  1. Computers & Graphics

    2 publications · 106 citations

    2

    h-index

  2. ACM Transactions on Graphics

    TOG · 2 publications · 149 citations

    2

    h-index

  3. The Visual Computer

    1 publications · 23 citations

    1

    h-index

  4. Computational Geometry

    1 publications · 15 citations

    1

    h-index

  5. Algorithmica

    1 publications · 98 citations

    1

    h-index

1–5