Graph-based Stitching

Graph-Based Stitching is a computational framework within image stitching that models pairwise image relationships as a graph structure, where nodes represent images and edges encode geometric or photometric constraints, enabling global consistency optimization through graph-based inference.

12

Publications

2.7K

Citations

46

Authors

22

Institutions

Publications per year

2017–2026

5

Authors

46

  1. IE
    Irfan Essa

    Georgia Institute of Technology, United States

    2 publications · 2K citations

    2

    h-index

  2. AB
    Aaron Bobick

    Georgia Institute of Technology, United States

    2 publications · 2K citations

    2

    h-index

  3. AE
    Ashley Eden

    University of California, Berkeley, United States

    2 publications · 501 citations

    2

    h-index

  4. AS
    Arno Schödl

    Georgia Institute of Technology, United States

    2 publications · 2K citations

    2

    h-index

  5. MU
    Matt Uyttendaele

    Microsoft (United States), United States

    2 publications · 501 citations

    2

    h-index

1–5 of 46

Venues

  1. IEEE/ACM Transactions on Networking

    TON · 1 publications · 16 citations

    1

    h-index

  2. 1

    h-index

  3. HAL (Le Centre pour la Communication Scientifique Directe)

    Repository · 1 publications · 11 citations

    1

    h-index

  4. Remote Sensing

    1 publications · 21 citations

    1

    h-index

  5. ACM Transactions on Graphics

    TOG · 1 publications · 770 citations

    1

    h-index

1–5