Method for Text Input with Google Cardboard: An Approach Using Smartwatches and Continuous Gesture Recognition

Method for Text Input with Google Cardboard: An Approach Using Smartwatches and Continuous Gesture Recognition

Abstract

This work proposes a method that allows the entry of text using the Google Cardboard, for this, uses gestures based on geometric forms and smartwatches. Thus, it is proposed the development of a prototype with the purpose of inserting a letter with no more than two user interactions. Gesture recognition is performed using the incremental recognition algorithm. After recognizing the gestures, they are sent to a classifier Naïve Bayes which is responsible for predicting the letter that will be inserted. The Naïve Bayes classifier was trained with a user gesture base that drew all the letters of the alphabet using only the gestures available in the set presented to them. Using the gesture base and the Naïve Bayes classifier a prototype for smartwatches was developed that works in conjunction with the Google Cardboard. The user performs the interactions on smartwatch and views them on Google Cardboard. This prototype automatically suggests the most likely letters to be entered and allows the user to enter text without having to look at smartwatch thus allowing the user to continue performing his other tasks.

Publication
In 2017 XIX Symposium on Virtual and Augmented Reality (SVR)
Date
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Accepted for publication.