Give Me a Hand: Improving the Effectiveness of Near-field Augmented Reality Interactions By Avatarizing Users' End Effectors
Roshan Venkatakrishnan, Rohith Venkatakrishnan, Balagopal Raveendranath, Christopher C. Pagano, Andrew C. Robb, Wen-Chieh Lin, Sabarish V. Babu
Abstract
Inspired by previous works showing promise for AR self-avatarization - providing users with an augmented self avatar, we investigated whether avatarizing users' end-effectors (hands) improved their interaction performance on a near-field, obstacle avoidance, object retrieval task wherein users were tasked with retrieving a target object from a field of non-target obstacles for a number of trials. We employed a 3 (Augmented hand representation) X 2 (density of obstacles) X 2 (size of obstacles) X 2 (virtual light intensity) multi-factorial design, manipulating the presence/absence and anthropomorphic fidelity of augmented self-avatars overlaid on the user's real hands, as a between subjects factor across three experimental conditions: (1) No-Augmented Avatar (using only real hands); (2) Iconic-Augmented Avatar; (3) Realistic Augmented Avatar. Results indicated that self-avatarization improved interaction performance and was perceived as more usable regardless of the anthropomorphic fidelity of avatar. We also found that the virtual light intensity used in illuminating holograms affects how visible one's real hands are. Overall, our findings seem to indicate that interaction performance may improve when users are provided with a visual representation of the AR system's interacting layer in the form of an augmented self-avatar.
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