Examination of the Effect of the Real-Life Meaning of the Stimulus on the Self-Motion Illusion

Moyou Jiang, Xuanru Guo, Takeharu Senoo, Gerard B. Remijn, Shinji Nakamura

Research output: Contribution to journalArticlepeer-review

Abstract

Vection refers to the illusory self-motion perception mainly induced by the motion of a visual stimulus. This phenomenon concerns presence and immersion in the illusion of self-motion, especially in vir tual reality. In the present study, we investigated how the real-life meaning of stimuli contributes to vection by using animations of objects that can move by themselves. In two psychophysical experiments, we first employed animated cars presented with or without wheel rotation as the visual inducer, using various motion directions and postures; then we added the road scenery, which was either moving (in the same or opposite direction to the cars) or still, as a contextual background in the visual stimulus. The results of Experiment 1 showed that in conditions with forward-and backward-moving cars, vection was stronger than in conditions with upward-moving and inver ted cars. The results of Experiment 2 showed that vection was weakest in the still road scenery condition and that the cars’ wheel rotation could facilitate vection. This suggests that the more natural the stimulus meanings, the stronger the vection. It is a feasible and effective application prospect to enhance the vection experience by changing the naturalness of the stimulus to fur ther increase the sense of presence and immersion. Therefore, the perceived naturalness and the assumed immobility of the visual inducer are two impor tant cognitive factors in visual self-motion perception and presence in the vir tual world.

Original languageEnglish
Pages (from-to)145-160
Number of pages16
JournalPresence: Teleoperators and Virtual Environments
Volume33
DOIs
Publication statusPublished - Dec 1 2024

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition

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