Title
Detecting Surface Interactions via a Wearable Microphone to Improve Augmented Reality Text Entry
Date of Award
2021
Document Type
Open Access Master's Thesis
Degree Name
Master of Science in Computer Science (MS)
Administrative Home Department
Department of Computer Science
Advisor 1
Keith Vertanen
Advisor 2
Scott Kuhl
Committee Member 1
Guy Hembroff
Abstract
This thesis investigates whether we can detect and distinguish between surface interaction events such as tapping or swiping using a wearable mic from a surface. Also, what are the advantages of new text entry methods such as tapping with two fingers simultaneously to enter capital letters and punctuation? For this purpose, we conducted a remote study to collect audio and video of three different ways people might interact with a surface. We also built a CNN classifier to detect taps. Our results show that we can detect and distinguish between surface interaction events such as tap or swipe via a wearable mic on the user's head.
Recommended Citation
Habibi, R., "Detecting Surface Interactions via a Wearable Microphone to Improve Augmented Reality Text Entry", Open Access Master's Thesis, Michigan Technological University, 2021.
Included in
Artificial Intelligence and Robotics Commons, Graphics and Human Computer Interfaces Commons