Evidence map›Paper›PMID 30695076›Full record

ArticlePloS one2019

Automatic classification of human facial features based on their appearance.

Felix Fuentes-Hurtado, Jose A Diego-Mas, Valery Naranjo, Mariano Alcañiz

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Felix Fuentes-HurtadoI3B - Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, Valencia, Spain.
Jose A Diego-MasI3B - Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, Valencia, Spain.ORCID 0000-0002-3698-3411
Valery NaranjoI3B - Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, Valencia, Spain.
Mariano AlcañizI3B - Institute for Research and Innovation in Bioengineering, Universitat Politècnica de València, Valencia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Classification or typology systems used to categorize different human body parts have existed for many years. Nevertheless, there are very few taxonomies of facial features. Ergonomics, forensic anthropology, crime prevention or new human-machine interaction systems and online activities, like e-commerce, e-learning, games, dating or social networks, are fields in which classifications of facial features are useful, for example, to create digital interlocutors that optimize the interactions between human and machines. However, classifying isolated facial features is difficult for human observers. Previous works reported low inter-observer and intra-observer agreement in the evaluation of facial features. This work presents a computer-based procedure to automatically classify facial features based on their global appearance. This procedure deals with the difficulties associated with classifying features using judgements from human observers, and facilitates the development of taxonomies of facial features. Taxonomies obtained through this procedure are presented for eyes, mouths and noses.

Indexed as

ClassificationEyeFaceFemaleHumansImage Processing, Computer-AssistedMaleMouthNosePattern Recognition, Automated

Identifiers

PMID30695076
PMCPMC6350975

What OpenQuestion holds

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LicenceCC BY
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.