Scale-invariant Matching

Scale-Invariant Matching is a template matching technique that enables the detection of a target pattern within an image regardless of variations in scale by normalizing or adapting to size differences between the template and the underlying scene.

147

Publications

81.4K

Citations

432

Authors

215

Institutions

Publications per year

2017–2026

27

Authors

432

  1. DL
    David Lowe

    University of British Columbia, Canada

    5 publications · 72.6K citations

    5

    h-index

  2. JM
    Jean‐Michel Morel

    École Normale Supérieure Paris-Saclay, France

    4 publications · 104 citations

    4

    h-index

  3. TH
    Tal Hassner

    Open University of Israel, Israel

    3 publications · 152 citations

    3

    h-index

  4. HL
    Hyon Lim

    Seoul National University, South Korea

    3 publications · 211 citations

    3

    h-index

  5. JJ
    James J. Little

    University of British Columbia, Canada

    3 publications · 1.1K citations

    3

    h-index

1–5 of 432

Venues

  1. Pattern Recognition

    6 publications · 302 citations

    6

    h-index

  2. 5

    h-index

  3. Electronics Letters

    3 publications · 66 citations

    3

    h-index

  4. IEEE Transactions on Image Processing

    3 publications · 209 citations

    3

    h-index

  5. International Journal of Computer Vision

    3 publications · 55.5K citations

    3

    h-index

1–5