Distance Estimation with Social Distancing: A Mobile Augmented Reality Study

Soumyajit Chakraborty ¹, Jeanine K. Stefanucci ², Sarah Creem-Regehr ², and Bobby Bodenheimer ^{1
1 Vanderbilt University, 2 University of Utah}

Although Augmented Reality (AR) can be easily implemented with most smartphones and tablets today, the investigation of distance perception with these types of devices has been limited. In this paper, we question whether the distance of a virtual human, e.g., avatar, seen through a smartphone or tablet display is perceived accurately. We also investigate, due to the Covid-19 pandemic and increased sensitivity to distances to others, whether a coughing avatar that either does or does not have a mask on affects distance estimates compared to a static avatar. We performed an experiment in which all participants estimated the distances to avatars that were either static or coughing, with and without masks on. Avatars were placed at a range of distances that would be typical for interaction, i.e., action space. Data on judgments of distance to the varying avatars was collected in a distributed manner by deploying an app for smartphones. Results showed that participants were fairly accurate in estimating the distance to all avatars, regardless of coughing condition or mask condition. Such findings suggest that mobile AR applications can be used to obtain accurate estimations of distances to virtual others “in the wild,” which is promising for using AR for simulations and training applications that require precise distance estimates.

Presented this paper at PERCXR workshop at IEEE VR 2021. Here is the link of the paper. The talk can be found below.