A Gesture Elicitation Study for Selection of Nail Size Objects in a Dense and Occluded Dense HMD-VR.
Shimmila Bhowmick, Pratul Chandra Kalita, Keyur Babulal Sorathia · 2020
Object selection is a fundamental and primary task in any Virtual Environment (VE). However, object selection in dense VEs presents challenges of inaccurate selection, higher error rates and increased task completion times. The challenges are further amplified when target objects are small as nail size, occluded and located at different distances from users. In this paper, we present a two-stage elicitation study for object selection in 4 dense VEs (2x2 selection conditions: the selection of near vs distant objects; with or without occlusion) in a Head-Mounted Display (HMD) based Virtual Reality (VR) platform. In study 1, we identified the most natural and intuitive gestures through a user-generated gesture study. In total, 737 gestures and 23, 29, 26 and 36 unique gestures were collected from 40 participants for mentioned VEs. We calculated an overall score to elucidate further a total of 3, 2, 3 and 3 gestures. In study 2, a new group of 33 participants rated these gestures on ease of performance, gesture appropriateness, body-part suitability and ranked them for user preferences and effort. Finally, we elucidate them to present one gesture each for each VE based on the results obtained from the study 2. We present and discuss the findings of preferences of upper body gestures, a strong emphasis on the confirmation, bringing targets within hands reach and non-occluded, accuracy over effort, scale manipulation of the VE and influence and adoption of WIMP and touch interfaces.