ObserVAR: Visualization System for Observing Virtual Reality Users using Augmented Reality

IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2019 DOI

Abstract

While virtual reality (VR) tools provide an immersive learning experience for students, it is difficult for an instructor to observe the students’ learning activities in a virtual environment (VE). Thus, it hinders interactions that could occur between the instructor and students, which are usually required in a classroom environment to understand how each student learns. Previous work has added virtual awareness cues that can help a small group of students to collaborate in a VE. However, when the number of students increases, such virtual awareness cues can cause visual clutter and confuse the instructor. We propose ObserVAR, a visualization system that allows the instructor to observe students in a VE at scale. ObserVAR uses augmented reality techniques to visualize each student’s gaze in a VE and improves the instructor’s awareness of the entire class. The visualizations are then optimized to reduce visual clutter in the scene using a force-directed graph drawing algorithm. In designing ObserVAR, we first investigated visualizations that can provide the instructor with an overall awareness of the VE that can be scaled up as the number of users increases. Second, we optimized the visualization of students by leveraging a graph drawing algorithm to reduce the visual clutter in the class scene. We compared the performance of our prototype with some commercially available user interfaces for VE classrooms. In our study, ObserVAR has demonstrated improvement and flexibility in several application scenarios.

Bibtex

@inproceedings{2019-observar,
  title = {{ObserVAR: Visualization System for Observing Virtual Reality Users using Augmented Reality}},
  author = {Santawat Thanyadit AND Parinya Punpongsanon AND Ting-Chuen Pong},
  booktitle = {IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
  year = {2019},
  doi = {10.1109/ISMAR.2019.00023},
  url = {https://www.fip.ics.saitama-u.ac.jp/pubs/observar}
}

Teaser/Talk