Examining Effects of Technique Awareness on the Detection of Remapped Hands in Virtual Reality
Brett Benda, Benjamin Rheault, Yanna Lin, Eric D. Ragan
Abstract
Input remapping techniques have been widely explored to allow users in virtual reality to exceed both their own physical abilities, the limitations of physical space, or to facilitate interactions with real-world objects. Often considered is how these techniques can be applied to achieve maximum utility, but still be undetectable to users to maintain a sense of immersion and presence. Existing psychophysical methods used to determine these detection thresholds have known limitations: they are highly conservative lower bounds for detection and do not account for complex usage of the technique. Our work describes and evaluates a method for estimating detection that reduces these limitations and yields meaningful upper bounds. We present the findings of our work where we apply this method to a well-explored hand motion scaling technique. In wholly unaware cases, we determined that users may detect their hand speed as abnormal at around 3.37 times the normal speed, compared to a scale factor of 1.47 that was estimated using traditional methods when users knew the motion scaling was occurring. A considerable number of participants in unaware cases (12 of 56) never detected their hand speed increasing at all, even at the maximum scale factor of 5.0. The study demonstrates just how conservative the thresholds generated by traditional psychophysical methods can be compared to detection during naive usage, and our method can be modified and applied easily to other techniques.
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