A QoE Evaluation of an Augmented Reality Procedure Assistance Application
| Autor: | Ronan Flynn, Niall Murray, Eoghan Hynes, Brian Lee |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
media_common.quotation_subject Quality of experience augmented reality headrotation frequency affective state Department of Computer and Software Engineering Athlone Institute of Technology Athlone Ireland Anger Task (project management) Identification (information) Expression (architecture) Human–computer interaction Augmented reality Quality (business) Metric (unit) media_common |
| Zdroj: | QoMEX |
| DOI: | 10.1109/qomex48832.2020.9123097 |
| Popis: | Augmented reality (AR) is a key technology to enhance worker effectiveness during increasing automation of repetitive jobs in the workplace. AR will achieve this by assisting the user to successfully perform complex and frequently changing procedures. The design of AR applications for these roles is critical to their acceptability and utility. User quality of experience (QoE) will inform these design decisions. A user arrives at a quality judgment upon post-experience reflection of their degree of delight or annoyance relating to the degree of fulfilment of pragmatic and hedonic needs and expectations of the medium under consideration. QoE researchers have largely depended upon post-experience subjective reports to determine the user's QoE. Subjective reports have been shown to be biased by primacy, recency and maxima of experience stimuli. Recent research involves the identification of implicit metrics that can be used to determine user QoE continuously during a multimedia experience. This work evaluates head rotation frequency as an objective metric of user QoE. The literature shows that emotion is expressed in the frequency of a person's head rotation around three axes of movement (pitch, yaw and roll). Low frequency head rotation has been shown to include expression of happy emotion while high frequency exclusively expresses anger emotion. These emotions are analogous to those reflected on by a user during the quality formation process. This demo paper analyses the amount of high frequency head rotation exhibited by the user upon task completion using an AR procedure assistance application or a paper-based control. An optimal Rubik's Cube solving AR application was used as a proof of concept for AR-based procedure assistance. Preliminary results showed that the AR environment yielded higher task success rates and significantly shorter task completion durations. The AR users exhibited significantly lower amplitudes of anger frequencies in their head rotations than the control group. |
| Databáze: | OpenAIRE |
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