Tap Model to Improve Input Accuracy of Touch Panels

In recent years, devices that use touch panels as interfaces, such as smart phones and tablet PCs, have spread. These devices have many advantages. For example, operating the panel can be done more intuitively in comparison with using conventional physical buttons, and the devices are quite more flexible than those that use a traditional fixed UI. However, mistakes frequently occur when inputting with a touch panel because the buttons have no physical boundaries and users cannot get tactile feedback with their fingers because the panels never change physically. Thus, the input accuracy of touch-panel devices is lower than that of devices with physical buttons. There are studies on improving input accuracy. Most of them use language models for typing natural language or probabilistic models to describe the errors made when users tap their fingers. However, these models are not practical, and the experiments are preliminary. Thus, in this paper, we propose a more practical model for improving input accuracy, in which the relative relationships between a target object and neighbor object that might influence error making when touching the target are tested. We consider that our model can describe important properties for designing various UIs depending on practical applications. We then make a plan to conduct experiments in order to build our model in a calibrated way and discuss our evaluation of the model.