Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective

要旨

Blind people have limited access to information about their surroundings, which is important for ensuring one's safety, managing social interactions, and identifying approaching pedestrians. With advances in computer vision, wearable cameras can provide equitable access to such information. However, the always-on nature of these assistive technologies poses privacy concerns for parties that may get recorded. We explore this tension from both perspectives, those of sighted passersby and blind users, taking into account camera visibility, in-person versus remote experience, and extracted visual information. We conduct two studies: an online survey with MTurkers (N=206) and an in-person experience study between pairs of blind (N=10) and sighted (N=40) participants, where blind participants wear a working prototype for pedestrian detection and pass by sighted participants. Our results suggest that both of the perspectives of users and bystanders and the several factors mentioned above need to be carefully considered to mitigate potential social tensions.

キーワード
wearable camera
accessibility
social acceptance
pedestrian detection
face recognition
crowdsourcing
著者
Kyungjun Lee
University of Maryland, College Park, MD, USA
Daisuke Sato
Carnegie Mellon University, Pittsburgh, PA, USA
Saki Asakawa
New York University, New York City, NY, USA
Hernisa Kacorri
University of Maryland, College Park, MD, USA
Chieko Asakawa
Carnegie Mellon University & IBM, Pittsburgh, PA, USA
DOI

10.1145/3313831.3376398

論文URL

https://doi.org/10.1145/3313831.3376398

動画

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: Automotive & pedestrian interfaces

Paper session
317AB KAHO'OLAWE
5 件の発表
2020-04-27 23:00:00
2020-04-28 00:15:00
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