Bayesian Touch - A Statistic Criterion of Target Selection with Finger Touch
Venue
Proceedings of UIST 2013 – The ACM Symposium on User Interface Software and Technology, ACM, New York, NY, USA, pp. 51-60
Publication Year
2013
Authors
BibTeX
Abstract
To improve the accuracy of target selection for finger touch, we conceptualize
finger touch input as an uncertain process, and derive a statistical target
selection riterion, Bayesian Touch Criterion, from combining the basic Bayes’ rule
of probability with the generalized dual Gaussian distribution hypothesis of finger
touch. Bayesian Touch Criterion states that the selected target is the candidate
with the shortest Bayesian Touch Distance to the touch point, which is computed
from the touch point to target center distance and the size of the target. We give
the derivation of the Bayesian touch criterion and its empirical evaluation with
two experiments. The results show for 2D circular target selection, Bayesian Touch
Criterion is significantly more accurate than the commonly used Visual Boundary
Criterion (i.e., a target is selected if and only if the touch point falls within
its boundary) and its two variants.
