The Efficacy of Discrepancy in Computer Graphics
M Patel - ACM SIGGRAPH 2023 Talks, 2023 - dl.acm.org
M Patel
ACM SIGGRAPH 2023 Talks, 2023•dl.acm.orgIn this presentation, we survey modern discrepancy metrics and use them to estimate the
quality of point sets produced from a variety of sample generators in two dimensions. Then,
we calculate the actual performance of these point sets for integrating a number of signals in
the unit square. Finally, we correlate the estimated performance to the observed result to
determine which metrics have the greatest utility as predictors of success for computer
graphics applications.
quality of point sets produced from a variety of sample generators in two dimensions. Then,
we calculate the actual performance of these point sets for integrating a number of signals in
the unit square. Finally, we correlate the estimated performance to the observed result to
determine which metrics have the greatest utility as predictors of success for computer
graphics applications.
In this presentation, we survey modern discrepancy metrics and use them to estimate the quality of point sets produced from a variety of sample generators in two dimensions. Then, we calculate the actual performance of these point sets for integrating a number of signals in the unit square. Finally, we correlate the estimated performance to the observed result to determine which metrics have the greatest utility as predictors of success for computer graphics applications.
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