Modeling the Endpoint Uncertainty in Crossing-based Moving Target Selection

Modeling the endpoint uncertainty of moving target selection with crossing is essential to understand factors such as speed-accuracy trade-off and interaction efficiency in crossing-based user interfaces with dynamic contents. However, there have been few studies looking into this research topic in the HCI field. This paper presents a Quaternary-Gaussian model to quantitatively measure the endpoint uncertainty in crossing-based moving target selection. To validate this model, we conducted an experiment with discrete crossing tasks on five factors, i.e., initial distance, size, speed, orientation, and moving direction. Results showed that our model fit the data of mu and sigma accurately with adjusted R-2 of 0.883 and 0.920. We also demonstrated the validity of our model in predicting error rates in crossing-based moving target selection. We concluded with a set of implications for future designs.