Revisiting detection thresholds for redirected walking: combining translation and curvature gains

Abstract

Redirected walking enables the exploration of large virtual environments while requiring only a finite amount of physical space. Unfortunately, in living room sized tracked areas the effectiveness of common redirection algorithms such as Steer-to-Center is very limited. A potential solution is to increase redirection effectiveness by applying two types of perceptual manipulations (curvature and translation gains) simultaneously. This paper investigates how such combination may affect detection thresholds for curvature gain. To this end we analyze the estimation methodology and discuss selection process for a suitable estimation method. We then compare curvature detection thresholds obtained under different levels of translation gain using two different estimation methods: method of constant stimuli and Green's maximum likelihood procedure. The data from both experiments shows no evidence that curvature gain detection thresholds were affected by the presence of translation gain (with test levels spanning previously estimated interval of undetectable translation gain levels). This suggests that in practice currently used levels of translation and curvature gains can be safely applied simultaneously. Furthermore, we present some evidence that curvature detection thresholds may be lower that previously reported. Our estimates indicate that users can be redirected on a circular arc with radius of either 11.6m or 6.4m depending on the estimation method vs. the previously reported value of 22m. These results highlight that the detection threshold estimates vary significantly with the estimation method and suggest the need for further studies to define efficient and reliable estimation methodology.