Perceptual Optimization

Perceptual Optimization is a computational framework that leverages models of human sensory and cognitive processing to prioritize and allocate system resources in augmented reality such that perceptually salient elements are rendered with higher fidelity while minimizing imperceptible artifacts and computational overhead.

75

Publications

3.1K

Citations

238

Authors

98

Institutions

Publications per year

2017–2026

26

Authors

238

  1. WL
    Weisi Lin

    Nanyang Technological University, Singapore

    3 publications · 173 citations

    3

    h-index

  2. KN
    King Ngi Ngan

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 123 citations

    3

    h-index

  3. BD
    Bodin Dresevic

    Microsoft (United States), United States

    2 publications · 124 citations

    2

    h-index

  4. GH
    Greg Hitchcock

    Microsoft (United States), United States

    2 publications · 124 citations

    2

    h-index

  5. DP
    Don P. Mitchell

    AT&T (United States), United States

    2 publications · 124 citations

    2

    h-index

1–5 of 238

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 4 publications · 240 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 104 citations

    4

    h-index

  3. 3

    h-index

  4. ACM Transactions on Graphics

    TOG · 2 publications · 171 citations

    2

    h-index

  5. Computer Graphics Forum

    2 publications · 47 citations

    2

    h-index

1–5