Task Breakpoint Generation using Origin-Centric Graph in Virtual Reality Recordings for Adaptive Playback
This method addresses the problem of automatic task segmentation in 3D VR environments, which is crucial for developing adaptive tutorials and authoring tools for AR/VR HMD users, representing an incremental improvement over existing 2D-restricted methods.
This paper introduces a method for automatically generating task breakpoints in goal-oriented VR activity recordings using an Origin-Centric Graph (OCG). The OCG tracks changes in central objects and group formations to segment assembly scenarios, achieving high agreement with user-perceived task breakpoints.
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.