  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.
