Accessing Passersby Proxemic Signals through a Head-Worn Camera: Opportunities and Limitations for the Blind
This addresses a critical need for blind people to navigate social interactions and personal space, though it appears incremental in applying existing computer vision methods to a specific assistive context.
The study tackled the problem of helping blind individuals access proxemic signals from passersby using a head-worn camera, analyzing data from 10 blind and 40 sighted participants to explore visual information, detection algorithms, and design implications.
The spatial behavior of passersby can be critical to blind individuals to initiate interactions, preserve personal space, or practice social distancing during a pandemic. Among other use cases, wearable cameras employing computer vision can be used to extract proxemic signals of others and thus increase access to the spatial behavior of passersby for blind people. Analyzing data collected in a study with blind (N=10) and sighted (N=40) participants, we explore: (i) visual information on approaching passersby captured by a head-worn camera; (ii) pedestrian detection algorithms for extracting proxemic signals such as passerby presence, relative position, distance, and head pose; and (iii) opportunities and limitations of using wearable cameras for helping blind people access proxemics related to nearby people. Our observations and findings provide insights into dyadic behaviors for assistive pedestrian detection and lead to implications for the design of future head-worn cameras and interactions.