Abstract

To create a self-motion (vection) situation in three-dimensional computer graphics (CG), there are mainly two ways: moving a camera toward an object (“camera moving”) or by moving the object and its surrounding environment toward the camera (“object moving”). As both methods vary considerably in the amount of computer calculations involved in generating CG, knowing how each method affects self-motion perception should be important to CG-creators and psychologists. Here, we simulated self-motion in a virtual three-dimensional CG-world, without stereoscopic disparity, which correctly reflected the lighting and glare. Self-motion was induced by “camera moving” or by “object moving,” which in the present experiments was done by moving a tunnel surrounding the camera toward the camera. This produced two retinal images that were virtually identical in Experiment 1 and very similar in Experiments 2 and 3. The stimuli were presented on a large plasma display to 15 naive participants and induced substantial vection. Three experiments comparing vection strength between the two methods found weak but significant differences. The results suggest that when creating CG visual experiences, “camera-moving” induces stronger vection.

Highlights

  • When a large visual field is occupied by coherent motion, we can perceive self-motion even though we do not move at all

  • What happens when we need to interpret a situation like the train illusion in a virtual computer graphics (CG) world where no extra cues exist to help you solve the perceptual ambiguity?

  • The main purpose of this study was to examine whether the virtually identical retinal images that resulted from the “camera moving” and the “tunnel moving” condition could induce vection in totally the same manner or not

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Summary

Introduction

When a large visual field is occupied by coherent motion, we can perceive self-motion even though we do not move at all. This illusory self-motion perception induced by visual stimuli is named vection. The train illusion is inevitably ambiguous because both perceptual solutions could be correct. You can eliminate the ambiguity by looking around the environment where cues exist that can help you determine which perceptual solution is correct (e.g., if the doors of your train are open, it can be a cue that your train is not moving). What happens when we need to interpret a situation like the train illusion in a virtual computer graphics (CG) world where no extra cues exist to help you solve the perceptual ambiguity?

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