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University of Ontario Institute of Technology

Comparison of performance for visual feedback and cursors in mid-air grasping of 3D objects

Abstract

dc:description.abstract

While investigating the performance benefits of visual feedback for grasping in midair interaction based virtual reality simulations, some studies noted that user performance in tasks has not improved when using visual feedback methods, while it has improved in other, similar studies. This thesis presents an experiment that was conducted to investigate the effectiveness of these techniques. The experiment itself involves a simple task that uses tools through a grasp and release mechanism, in a virtual environment that compares visual feedback methods used in other studies against techniques meant to inform the user of the bounds of the simulation in advance, known as feedforward techniques. Data collected finds that performance is not significantly impacted by either feedback or feedforward techniques, though feedback is preferred against a lack of feedback. Recommendations are provided to help minimize the use of visual effects on objects that may draw user focus from their intended target.

Degree

thesis:*
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 and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Culver, Claire Madilyn
Advisor dc:contributor.advisor
  • Kapralos, Bill

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1823
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1823

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Culver, Claire Madilyn. Comparison of performance for visual feedback and cursors in mid-air grasping of 3D objects. University of Ontario Institute of Technology, 2024. https://hdl.handle.net/10155/1823