Evaluation on Different Object Selection Visual Feedback in Collaborative Augmented Reality

Collaborative Augmented Reality (CAR) involves multiple users working together in an augmented reality setting to accomplish tasks. In CAR, transparent techniques enable users to see occluded objects in complex environments, yet they often struggle to discern which part of a complex object they have selected. Workspace awareness refers to understanding how others interact within a shared workspace and influence the choice of visualization techniques. This study investigated workspace awareness regarding different object selection visual feedback in co-located CAR. It explored four technique variations: Hi (highlight), Hi-Ray (ray emitting), Hi-View (view switching), and Hi-RV (ray emitting and view switching). Thirty-two participants were divided into 16 pairs, with an instructor demonstrating how to assemble an engine component and a student replicating the process using the four visualization techniques. Results showed the visualization techniques did not affect task completion time significantly. The Hi and Hi-Ray technique had the highest error rate, while the Hi-RV technique had the lowest. However, users preferred the Hi-View technique, which scored highest in interaction, collaboration quality, workspace awareness, and required less workload. To enhance awareness, participants pointed out the weakness in the combination of visual feedback, particularly with the ray emitting technique, which causes confusion when multiple objects are selected due to visual clutter. They suggested that integrating audio feedback could help alert users to their choices, and using color-based indicators could distinguish different actions, such as indicating correct or incorrect placement of virtual objects.

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Publication Details

Journal
International Journal of Human-Computer Interaction
Published
2024-08-15
DOI
https://doi.org/10.1080/10447318.2024.2389727
Citations
4
Primary Topic
Augmented Reality Applications
Type
article
Field-Weighted Citation Impact
1.00

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article

Evaluation on Different Object Selection Visual Feedback in Collaborative Augmented Reality

Nazatul Aini Abd Majid, Nur Asylah Suwadi, Meng Chun Lam
4 citations
International Journal of Human-Computer Interaction
Augmented Reality Applications
1.00
article

Evaluation on Different Object Selection Visual Feedback in Collaborative Augmented Reality

Nazatul Aini Abd Majid, Nur Asylah Suwadi, Meng Chun Lam
article en
4 citations

Abstract

Collaborative Augmented Reality (CAR) involves multiple users working together in an augmented reality setting to accomplish tasks. In CAR, transparent techniques enable users to see occluded objects in complex environments, yet they often struggle to discern which part of a complex object they have selected. Workspace awareness refers to understanding how others interact within a shared workspace and influence the choice of visualization techniques. This study investigated workspace awareness regarding different object selection visual feedback in co-located CAR. It explored four technique variations: Hi (highlight), Hi-Ray (ray emitting), Hi-View (view switching), and Hi-RV (ray emitting and view switching). Thirty-two participants were divided into 16 pairs, with an instructor demonstrating how to assemble an engine component and a student replicating the process using the four visualization techniques. Results showed the visualization techniques did not affect task completion time significantly. The Hi and Hi-Ray technique had the highest error rate, while the Hi-RV technique had the lowest. However, users preferred the Hi-View technique, which scored highest in interaction, collaboration quality, workspace awareness, and required less workload. To enhance awareness, participants pointed out the weakness in the combination of visual feedback, particularly with the ray emitting technique, which causes confusion when multiple objects are selected due to visual clutter. They suggested that integrating audio feedback could help alert users to their choices, and using color-based indicators could distinguish different actions, such as indicating correct or incorrect placement of virtual objects.

International Journal of Human-Computer InteractionVol. 41(11)
National University of Malaysia (MY)
Universiti Kebangsaan Malaysia
Openalex Percentile: Top 23%
Augmented Reality Applications
1.00
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