Sickness Reduction in FPV Drone Control: Improved Effects of Reverse Optical Flow with Static Landmarks Only

Jun Ryu, Seunghoon Park, Gerard Jounghyun Kim

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

1 Citation (Scopus)

Abstract

Drones are controlled remotely through the on-board live camera often using a headset to immersively (without external distraction) situate the drone operator with a first-person view. The highly dynamic imagery of drone piloting can elicit significant VR sickness. In this poster, we demonstrate the application of mixing the reverse optical flow pattern into the drone piloting imagery for mitigating VR sickness, using only the features of the static landmarks in the scene. We compare it to the cases of applying no mitigation technique (baseline) and mixing in the optical flow pattern from "all"object features. The results show that the suggested method was significantly more effective in reducing sickness than when considering all object features, and had a higher preference for improved visibility and controllability.

Original languageEnglish
Title of host publicationVRST 2023 - 29th ACM Symposium on Virtual Reality Software and Technology
PublisherAssociation for Computing Machinery
ISBN (Electronic)9798400703287
DOIs
Publication statusPublished - 2023 Oct 9
Event29th ACM Symposium on Virtual Reality Software and Technology, VRST 2023 - Christchurch, New Zealand
Duration: 2023 Oct 92023 Oct 11

Publication series

NameProceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST

Conference

Conference29th ACM Symposium on Virtual Reality Software and Technology, VRST 2023
Country/TerritoryNew Zealand
CityChristchurch
Period23/10/923/10/11

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author.

Keywords

  • Drone
  • Object Detection
  • Optical Flow
  • VR Sickness
  • Virtual Reality

ASJC Scopus subject areas

  • Software

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