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
