Location-Based Non-Linear Playback of AR Task Recording

Bowen Yuan; Zirui Xiao; Hyunwoo Cho; Gun A. Lee; Mark Billinghurst

doi:10.1109/VRW70859.2026.00181

Location-Based Non-Linear Playback of AR Task Recording

Bowen Yuan^*
, Zirui Xiao
, Hyunwoo Cho
, Gun A. Lee
, Mark Billinghurst

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Augmented Reality (AR) systems that capture and replay user actions provide valuable support for training and task guidance by preserving activities within their original spatial context. However, reviewing AR recordings remains inefficient, as most systems rely on linear playback that requires time-consuming manual search. This project investigates a non-linear replay approach that automatically segments AR task recordings based on spatial location data. The system enables reviewers to navigate recordings by jumping directly to task segments associated with their current physical location. Preliminary findings from a user evaluation suggest that organizing AR recordings around spatial structure can better support task review and analysis, and provide a foundation for more efficient and usable AR training and evaluation systems. © 2026 IEEE.

Original language	English
Title of host publication	2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
Publisher	IEEE
Pages	1001-1004
Number of pages	4
ISBN (Electronic)	979-8-3195-0529-3
ISBN (Print)	979-8-3195-0530-9
DOIs	https://doi.org/10.1109/VRW70859.2026.00181
Publication status	Published - 2026
Event	33rd IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2026) - Daegu, Korea, Republic of Duration: 21 Mar 2026 → 25 Mar 2026 https://ieeevr.org/2026/

Publication series

Name	Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW

Conference

Conference	33rd IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2026)
Place	Korea, Republic of
City	Daegu
Period	21/03/26 → 25/03/26
Internet address	https://ieeevr.org/2026/

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

Asynchronous Collaboration
Location-Based Augmented Reality

Access Output

10.1109/VRW70859.2026.00181

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

Yuan, B., Xiao, Z., Cho, H., Lee, G. A., & Billinghurst, M. (2026). Location-Based Non-Linear Playback of AR Task Recording. In 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (pp. 1001-1004). (Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW). IEEE. https://doi.org/10.1109/VRW70859.2026.00181

@inproceedings{e0b19b5aed88472785ee49823645fb57,

title = "Location-Based Non-Linear Playback of AR Task Recording",

abstract = "Augmented Reality (AR) systems that capture and replay user actions provide valuable support for training and task guidance by preserving activities within their original spatial context. However, reviewing AR recordings remains inefficient, as most systems rely on linear playback that requires time-consuming manual search. This project investigates a non-linear replay approach that automatically segments AR task recordings based on spatial location data. The system enables reviewers to navigate recordings by jumping directly to task segments associated with their current physical location. Preliminary findings from a user evaluation suggest that organizing AR recordings around spatial structure can better support task review and analysis, and provide a foundation for more efficient and usable AR training and evaluation systems. {\textcopyright} 2026 IEEE.",

keywords = "Asynchronous Collaboration, Location-Based Augmented Reality",

author = "Bowen Yuan and Zirui Xiao and Hyunwoo Cho and Lee, \{Gun A.\} and Mark Billinghurst",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).; 33rd IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2026) ; Conference date: 21-03-2026 Through 25-03-2026",

year = "2026",

doi = "10.1109/VRW70859.2026.00181",

language = "English",

isbn = "979-8-3195-0530-9",

series = "Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW",

publisher = "IEEE",

pages = "1001--1004",

booktitle = "2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",

address = "United States",

url = "https://ieeevr.org/2026/",

}

Yuan, B, Xiao, Z, Cho, H, Lee, GA & Billinghurst, M 2026, Location-Based Non-Linear Playback of AR Task Recording. in 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW, IEEE, pp. 1001-1004, 33rd IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2026), Daegu, Korea, Republic of, 21/03/26. https://doi.org/10.1109/VRW70859.2026.00181

Location-Based Non-Linear Playback of AR Task Recording. / Yuan, Bowen; Xiao, Zirui; Cho, Hyunwoo et al.
2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 2026. p. 1001-1004 (Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Location-Based Non-Linear Playback of AR Task Recording

AU - Yuan, Bowen

AU - Xiao, Zirui

AU - Cho, Hyunwoo

AU - Lee, Gun A.

AU - Billinghurst, Mark

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2026

Y1 - 2026

N2 - Augmented Reality (AR) systems that capture and replay user actions provide valuable support for training and task guidance by preserving activities within their original spatial context. However, reviewing AR recordings remains inefficient, as most systems rely on linear playback that requires time-consuming manual search. This project investigates a non-linear replay approach that automatically segments AR task recordings based on spatial location data. The system enables reviewers to navigate recordings by jumping directly to task segments associated with their current physical location. Preliminary findings from a user evaluation suggest that organizing AR recordings around spatial structure can better support task review and analysis, and provide a foundation for more efficient and usable AR training and evaluation systems. © 2026 IEEE.

AB - Augmented Reality (AR) systems that capture and replay user actions provide valuable support for training and task guidance by preserving activities within their original spatial context. However, reviewing AR recordings remains inefficient, as most systems rely on linear playback that requires time-consuming manual search. This project investigates a non-linear replay approach that automatically segments AR task recordings based on spatial location data. The system enables reviewers to navigate recordings by jumping directly to task segments associated with their current physical location. Preliminary findings from a user evaluation suggest that organizing AR recordings around spatial structure can better support task review and analysis, and provide a foundation for more efficient and usable AR training and evaluation systems. © 2026 IEEE.

KW - Asynchronous Collaboration

KW - Location-Based Augmented Reality

UR - http://www.scopus.com/inward/record.url?scp=105038794766&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-105038794766&origin=recordpage

U2 - 10.1109/VRW70859.2026.00181

DO - 10.1109/VRW70859.2026.00181

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3195-0530-9

T3 - Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW

SP - 1001

EP - 1004

BT - 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)

PB - IEEE

T2 - 33rd IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2026)

Y2 - 21 March 2026 through 25 March 2026

ER -

Yuan B, Xiao Z, Cho H, Lee GA, Billinghurst M. Location-Based Non-Linear Playback of AR Task Recording. In 2026 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE. 2026. p. 1001-1004. (Proceedings - IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW). Epub 2026 May 1. doi: 10.1109/VRW70859.2026.00181

Location-Based Non-Linear Playback of AR Task Recording

Abstract

Publication series

Conference

Bibliographical note

Research Keywords

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this