Estimation of Brush Type Passive Stylus Angles Using Capacitive Image

Abstract

Smartphones have limited input vocabularies compared with PCs. In this paper, we propose a method for estimating the stylus angle of a passive brush from capacitive images. The technique allows us to expand the input vocabulary without complicating the smartphone or the stylus. We conducted experiments that showed the estimation error (MAE) was 6.63° for pitch and 5.97° for roll. Two applications were implemented to show the feasibility of the technique.