Abstract
When interacting with virtual reality (VR) applications like CAD and open-world games, people may want to use gestures as a means of leveraging their knowledge from the physical world. However, people may prefer physical props over handheld controllers to input gestures in VR. We present an elicitation study where 21 participants chose from 95 props to perform manipulative gestures for 20 CAD-like and open-world game-like referents. When analyzing this data, we found existing methods for elicitation studies were insufficient to describe gestures with props, or to measure agreement with prop selection (i.e., agreement between sets of items). We proceeded by describing gestures as context-free grammars, capturing how different props were used in similar roles in a given gesture. We present gesture and prop agreement scores using a generalized agreement score that we developed to compare multiple selections rather than a single selection. We found that props were selected based on their resemblance to virtual objects and the actions they afforded; that gesture and prop agreement depended on the referent, with some referents leading to similar gesture choices, while others led to similar prop choices; and that a small set of carefully chosen props can support multiple gestures.
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More From: Proceedings of the ACM on Human-Computer Interaction
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