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


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.

In 2017 XIX Symposium on Virtual and Augmented Reality (SVR)

Accepted for publication.

Thamer Nascimento
Thamer Nascimento
PhD Student
and former Master’s Student

Fabrizzio Soares is bla bla bla.

Fabrizzio Soares
Fabrizzio Soares
Associate Professor and CS Chair

Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.