Exploring gestural interaction in smart spaces using head mounted devices with ego-centric sensing

Abstract

It is now possible to develop head-mounted devices (HMDs) that allow for ego-centric sensing of mid-air gestural input. Therefore, we explore the use of HMD-based gestural input techniques in smart space environments. We developed a usage scenario to evaluate HMD-based gestural interactions and conducted a user study to elicit qualitative feedback on several HMD-based gestural input techniques. Our results show that for the proposed scenario, mid-air hand gestures are preferred to head gestures for input and rated more favorably compared to non-gestural input techniques available on existing HMDs. Informed by these study results, we developed a prototype HMD system that supports gestural interactions as proposed in our scenario. We conducted a second user study to quantitatively evaluate our prototype comparing several gestural and non-gestural input techniques. The results of this study show no clear advantage or disadvantage of gestural inputs vs.~non-gestural input techniques on HMDs. We did find that voice control as (sole) input modality performed worst compared to the other input techniques we evaluated. Lastly, we present two further applications implemented with our system, demonstrating 3D scene viewing and ambient light control. We conclude by briefly discussing the implications of ego-centric vs. exo-centric tracking for interaction in smart spaces.