Trajectory Prediction Model for Crossing-Based Target Selection.

In some cases, crossing-based target selection motion may gain a less error rates and a higher interactive speed. Most of the research in target selection fields focused on the analysis of interaction results. Moreover, trajectories play a much more important role in crossing-based target selection comparing to the other interactive techniques. And an ideal model for trajectories may help computer designers make predictions about interaction results during the process of target selection rather than at the end of the whole process. We proposed a trajectory prediction model for crossing-based target selection tasks referring to dynamic model theory. Simulation results show that our model performed well in the prediction of the trajectories, endpoints and the hitting time for target-selection motion, and the average error of trajectories, endpoints and hitting time values as 17.28%, 18.17 pixel and 11.50%.