What is it about?
A novel model for describing endpoint uncertainty when pointing at moving targets of arbitrary shapes, based on the idea of combining the uncertainty related to the target shape with the uncertainty caused by the target motion.
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Why is it important?
We proposed a model to predict endpoint distribution on static targets based on a Dual-Space Decomposition (DUDE) algorithm. We linearly combined a 2D Ternary-Gaussian model with the newly proposed DUDE-based model to make the 2D Ternary-Gaussian model adaptable to moving targets with random shapes.
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This page is a summary of: Shape-Adaptive Ternary-Gaussian Model: Modeling Pointing Uncertainty for Moving Targets of Arbitrary Shapes, April 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3544548.3581217.
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