Redefining the human factors approach to 3D gestural HCI by exploring the usability-accuracy tradeoff in gestural computer systems

3D gestural technology for HCI could transform the way people interact with computing systems. There are traditionally two approaches to developing gestural technology systems: a human-based approach where usability is maximized and a technology-based approach where system accuracy is maximized. The tradeoff between usability and accuracy may negatively affect the overall trust and reliability in the system. Therefore, this study seeks to redefine the human-based approach to gestural system development by introducing a bottom-up approach to identifying the lower-level features that produce a gesture, thus allowing the technology to accurately recognize features. A user elicitation study was performed, and gestures were classified according to a novel feature extraction gesture taxonomy and a traditional taxonomy of classifying gestures as a unit. The feature-extraction approach revealed several advantages because it fosters a bottom-up approach to identifying gesture features. Using this approach may mitigate the effects of the usability-accuracy tradeoff in gestural system development.