Recognition of typing motions on AR typing interface

We have proposed Augmented Reality (AR) Typing Interface as a new input interface for mobile devices. By using this interface, users can utilize a wide space in the air in inputting texts. This interface uses a camera which is attached to the back of the device. A virtual keyboard is overlaid on the image captured by a camera using AR technology. In this paper, we propose a new method to recognize typing motions more precisely. In this method, feature vectors are generated by using information of time-series optical flows. Typing motions are recognized by using support vector machine (SVM). We confirmed that the proposed method was able to recognize typing motions with about 90% accuracy for the recorded video of typing in the air.