Characterizing midair handwriting in virtual reality

Midair handwriting poses challenges due to the lack of a physical plane to press against while writing, making it difficult to determine when ink should be placed. In this thesis, we gathered midair handwriting data from 24 participants in an environment that allowed them to write freely. We compared writing with a pen-like object and writing using a finger across two writing methods (writing freely versus on a virtual whiteboard). Using our data, we trained a neural network to detect when ink should be placed during midair handwriting, achieving an overall 85% accuracy. We developed a data-viewing application to recreate sentences for visual analysis. Participant feedback favoured the pen-like object as a writing utensil, with equal preference for both writing methods. Our contributions include a midair handwriting Virtual Reality (VR) application for data collection, a dataset containing 480 sentences of frame-by-frame midair handwriting data, and 20 unique prompts used in participant trials.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Chan, Matthew

Advisors dc:contributor.advisor

• Collins, Christopher
• Qureshi, Faisal

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/1773

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/1773