Accessing Passersby Proxemic Signals through a Head-Worn Camera: Opportunities and Limitations for the Blind

TL;DR

This study explores how head-worn cameras can help blind individuals perceive nearby people's spatial behaviors, analyzing visual data and pedestrian detection algorithms to identify opportunities and limitations for assistive technology.

Contribution

It introduces an analysis of proxemic signals captured by wearable cameras and evaluates their potential for aiding blind people in social and spatial awareness.

Findings

Head-worn cameras can detect approaching passersby and their relative positions.

Pedestrian detection algorithms have limitations in complex or crowded environments.

Insights inform future design of assistive head-worn devices for spatial awareness.

Abstract

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.