Evidence map›Paper›PMID 36540857›Full record

ArticleImage and vision computing2023

A survey on computer vision based human analysis in the COVID-19 era.

Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakın, Naser Damer, Ferda Ofli, Muhammad Imran, Janez Križaj, Albert Ali Salah, Alexander Waibel, Vitomir Štruc and 1 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Image and vision computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.9field-weighted citation impact, top 12% of its field
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

1 citing paper in PubMed, 20 citations in OpenAlex.

  1. A Review on Face Mask Recognition.Sensors (Basel, Switzerland) · 2025
    Review
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

11 authors at 7 institutions in 6 countries.

Fevziye Irem EyiokurInstitute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Alperen KantarcıDepartment of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
Mustafa Ekrem ErakınDepartment of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
Naser DamerFraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany.
Ferda OfliQatar Computing Research Institute, HBKU, Doha, Qatar.
Muhammad ImranQatar Computing Research Institute, HBKU, Doha, Qatar.
Janez KrižajFaculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia.
Albert Ali SalahDepartment of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands.
Alexander WaibelInstitute for Anthropomatics and Robotics, Karlsruhe Institute of Technology, Karlsruhe, Germany.
Vitomir ŠtrucFaculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia.
Hazım Kemal EkenelDepartment of Computer Engineering, Istanbul Technical University, Istanbul, Turkey.
Istanbul Technical University · TRQatar Airways (Qatar) · QAUniversity of Ljubljana · SIBoğaziçi University · TRCarnegie Mellon University · USKarlsruhe Institute of Technology · DETechnical University of Darmstadt · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of screening applications. These developments also triggered the need for novel and improved computer vision techniques capable of

Indexed as

Computer visionCOVID-19Human analysisMasked facesSurvey

Identifiers

PMID36540857
PMCPMC9755265
OpenAlexW4313479194

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.