Keypoint-based Matching

Keypoint-Based Matching is a template matching method that identifies correspondences by detecting and comparing distinctive local feature points, distinguished from other methods through its reliance on invariant keypoint descriptors rather than direct pixel-wise or region-based similarity.

105

Publications

7.6K

Citations

356

Authors

150

Institutions

Publications per year

2017–2026

31

Authors

356

  1. AD
    Alberto Del Bimbo

    University of Florence, Italy

    3 publications · 119 citations

    3

    h-index

  2. LB
    Lamberto Ballan

    University of Florence, Italy

    2 publications · 79 citations

    2

    h-index

  3. AZ
    Andy Zeng

    Google (United States), United States

    2 publications · 2.1K citations

    2

    h-index

  4. MS
    Manolis Savva

    Stanford University, United States

    2 publications · 2.1K citations

    2

    h-index

  5. MB
    Marco Bertini

    University of Florence, Italy

    2 publications · 79 citations

    2

    h-index

1–5 of 356

Venues

  1. 4

    h-index

  2. Procedia Computer Science

    3 publications · 62 citations

    3

    h-index

  3. Multimedia Tools and Applications

    3 publications · 76 citations

    3

    h-index

  4. IEEE Transactions on Image Processing

    3 publications · 78 citations

    3

    h-index

  5. IEEE Geoscience and Remote Sensing Letters

    GRSL · 2 publications · 576 citations

    2

    h-index

1–5