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
75
Perceptual models of preference in 3D printing direction
Xiaoting Zhang, Xinyi Le, Athina Panotopoulou et al. · ACM Transactions on Graphics · 2015 · 137 citations
Engineering, Manufacturing Engineering, Materials Science +16
1–5 of 75
238
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98
Chinese University of Hong Kong
Hong Kong, Hong Kong
4 h-index
9 publications
610 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
10 publications
540 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
10 publications
1.1K citations
Microsoft (United States)
Redmond, United States
3 h-index
13 publications
736 citations
Princeton University
Princeton, United States
2 h-index
2 publications
102 citations
Texas A&M University
College Station, United States
2 h-index
3 publications
74 citations

Ames Research Center
Mountain View, United States
2 h-index
3 publications
177 citations
Netflix (United States)
Los Gatos, United States
2 h-index
5 publications
232 citations
1–8 of 98
TVCG · 4 publications · 240 citations
4
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Repository · 4 publications · 104 citations
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3 publications · 159 citations
3
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TOG · 2 publications · 171 citations
2
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2 publications · 47 citations
2
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1–5