Path Prediction Using LSTM Network for Redirected Walking

Yang Hun Cha, Dang Yang Lee, In Kwan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Redirected walking enables immersive walking experience in a limited-sized room. To apply redirected walking efficiently and minimize the number of resets, an accurate path prediction algorithm is required. We propose a data-driven path prediction model using Long Short-Term Memory(LSTM) network. User path data was collected via path exploration experiment on a maze-like environment and fed into LSTM network. Our algorithm can predict user's future path based on user's past position and facing direction data. We compare our path prediction result with actual user data and show that our model can accurately predict user's future path.

Original languageEnglish
Title of host publication25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018 - Proceedings
EditorsFrank Steinicke, Bruce Thomas, Kiyoshi Kiyokawa, Greg Welch
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages527-528
Number of pages2
ISBN (Print)9781538633656
DOIs
Publication statusPublished - 2018 Aug 24
Event25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018 - Reutlingen, Germany
Duration: 2018 Mar 182018 Mar 22

Publication series

Name25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018 - Proceedings

Conference

Conference25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018
CountryGermany
CityReutlingen
Period18/3/1818/3/22

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Modelling and Simulation
  • Media Technology

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  • Cite this

    Cha, Y. H., Lee, D. Y., & Lee, I. K. (2018). Path Prediction Using LSTM Network for Redirected Walking. In F. Steinicke, B. Thomas, K. Kiyokawa, & G. Welch (Eds.), 25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018 - Proceedings (pp. 527-528). [8446442] (25th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VR.2018.8446442