Task Breakpoint Generation using Origin-Centric Graph in Virtual Reality Recordings for Adaptive Playback

Fuente: arXiv
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Autores principales: Choi, Selin, Kim, Dooyoung, Ha, Taewook, Kim, Seonji, Woo, Woontack
Formato: Preprint
Publicado: 2026
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author Choi, Selin
Kim, Dooyoung
Ha, Taewook
Kim, Seonji
Woo, Woontack
author_facet Choi, Selin
Kim, Dooyoung
Ha, Taewook
Kim, Seonji
Woo, Woontack
contents We propose a method for generating task breakpoints based on an Origin-Centric Graph (OCG) to segment goal-oriented activity recordings into task units for adaptive playback in Virtual Reality (VR) environments. With the development of Augmented Reality (AR)/VR head-mounted displays (HMDs), research on adaptive tutorials and authoring tools has become active, but existing task segmentation methods mainly rely on manual annotation or are restricted to 2D video which limits their applicability to 3D VR contexts. In our approach, assembly scenarios with clearly defined task boundaries are recorded using a structured spatio-temporal scene graph (STSG), and the OCG is employed to track changes in the central object and the formation of new groups, thereby generating task breakpoints automatically. A user study collected user-perceived task breakpoints to establish ground truth (GT), and comparison with the algorithm-detected breakpoints demonstrated high agreement and confirmed accuracy in supporting adaptive playback. The proposed task segmentation method provides a foundation for dynamically adjusting VR playback according to user proficiency and progress, with potential for extension into automatic timeline segmentation systems for diverse VR recordings.
format Preprint
id arxiv_https___arxiv_org_abs_2603_07627
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Task Breakpoint Generation using Origin-Centric Graph in Virtual Reality Recordings for Adaptive Playback
Choi, Selin
Kim, Dooyoung
Ha, Taewook
Kim, Seonji
Woo, Woontack
Human-Computer Interaction
We propose a method for generating task breakpoints based on an Origin-Centric Graph (OCG) to segment goal-oriented activity recordings into task units for adaptive playback in Virtual Reality (VR) environments. With the development of Augmented Reality (AR)/VR head-mounted displays (HMDs), research on adaptive tutorials and authoring tools has become active, but existing task segmentation methods mainly rely on manual annotation or are restricted to 2D video which limits their applicability to 3D VR contexts. In our approach, assembly scenarios with clearly defined task boundaries are recorded using a structured spatio-temporal scene graph (STSG), and the OCG is employed to track changes in the central object and the formation of new groups, thereby generating task breakpoints automatically. A user study collected user-perceived task breakpoints to establish ground truth (GT), and comparison with the algorithm-detected breakpoints demonstrated high agreement and confirmed accuracy in supporting adaptive playback. The proposed task segmentation method provides a foundation for dynamically adjusting VR playback according to user proficiency and progress, with potential for extension into automatic timeline segmentation systems for diverse VR recordings.
title Task Breakpoint Generation using Origin-Centric Graph in Virtual Reality Recordings for Adaptive Playback
topic Human-Computer Interaction
url https://arxiv.org/abs/2603.07627