Evidence map›Paper›PMID 35187543›Full record

ArticleASSETS. Annual ACM Conference on Assistive Technologies2021

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

Kyungjun Lee, Daisuke Sato, Saki Asakawa, Chieko Asakawa, Hernisa Kacorri

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ASSETS. Annual ACM Conference on Assistive Technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kyungjun LeeUniversity of Maryland, College Park, College Park, Maryland, USA.
Daisuke SatoCarnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Saki AsakawaNew York University, Brooklyn, New York, USA.
Chieko AsakawaIBM Research, Carnegie Mellon University.
Hernisa KacorriUniversity of Maryland, College Park, College Park, Maryland, USA.

Funding

ACL HHS 90REGE0008
6 · The paper itself

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.

Indexed as

Accessibility technologiesblind peopleComputing methodologies → Computer visionEmpirical studies in accessibilityEmpirical studies in HCIHuman-centered computing → User studiesmachine learningMobile devicespedestrian detectionproxemicsspatial proximitywearable camera

Identifiers

PMID35187543
PMCPMC8855357

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.