Marker Detection Optimization

Marker Detection Optimization is a methodological framework within augmented reality systems that enhances the efficiency and accuracy of identifying visual markers by minimizing computational overhead and maximizing robustness under varying environmental conditions.

11

Publications

442

Citations

42

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

42

  1. JD
    Jean Dumont

    Université de Pau et des Pays de l'Adour, France

    1 publications · 33 citations

    1

    h-index

  2. EK
    Etsuko Kobayashi

    The University of Tokyo, Japan

    1 publications · 20 citations

    1

    h-index

  3. KS
    Kosuke Sato

    The University of Osaka, Japan

    1 publications · 28 citations

    1

    h-index

  4. AA
    Andrea Albarelli

    Ca' Foscari University of Venice, Italy

    1 publications · 16 citations

    1

    h-index

  5. MB
    Mustafa B. Yaldiz

    Korea Advanced Institute of Science and Technology, South Korea

    1 publications · 14 citations

    1

    h-index

1–5 of 42

Venues

  1. 1

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  2. Journal of Biomechanics

    1 publications · 57 citations

    1

    h-index

  3. Radiotherapy and Oncology

    1 publications · 33 citations

    1

    h-index

  4. ACM Transactions on Graphics

    TOG · 1 publications · 14 citations

    1

    h-index

  5. 1

    h-index

1–5