Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

594
Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
594
Muscles for Facial Expressions01:14

Muscles for Facial Expressions

4.7K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
4.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Early Emergence of Spontaneous Trait Content in Children's Unconstrained Impressions of Faces.

Developmental science·2026
Same author

The sound of emergency: The role of vocal cues in healthcare.

Social science & medicine (1982)·2025
Same author

People calibrate future expectations to past performance when predicting transparently random events.

PNAS nexus·2025
Same author

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus.

Nature human behaviour·2025
Same author

Face evaluation: Findings, methods, and challenges.

Annals of the New York Academy of Sciences·2025
Same author

Individualized models of social judgments and context-dependent representations.

Scientific reports·2025

Related Experiment Video

Updated: Jan 17, 2026

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children
05:04

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

Published on: October 4, 2018

7.3K

Capturing variability in children's faces: an artificial, yet realistic, face stimulus set.

Sophia M Thierry1, Stefan Uddenberg2, Daniel Albohn3

  • 1Department of Psychology, Brock University, St. Catharines, ON, Canada.

Frontiers in Psychology
|September 18, 2025
PubMed
Summary
This summary is machine-generated.

A new dataset of 500 artificial children's faces, diverse in age and ethnicity, has been created. This resource addresses the underrepresentation of child faces in current research databases.

Keywords:
artificial face generationchildrenemotionsexpressionsface database

More Related Videos

Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

21.9K
Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
07:09

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

11.4K

Related Experiment Videos

Last Updated: Jan 17, 2026

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children
05:04

An Electrophysiology Protocol to Measure Reward Anticipation and Processing in Children

Published on: October 4, 2018

7.3K
Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

21.9K
Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior
07:09

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Published on: November 14, 2018

11.4K

Area of Science:

  • Computer Vision
  • Developmental Psychology
  • Human-Computer Interaction

Background:

  • Existing child face datasets are limited in size and diversity.
  • Underrepresentation of children's faces hinders research in developmental psychology and AI.
  • A need exists for a comprehensive and diverse dataset of children's faces.

Purpose of the Study:

  • To create a novel, large-scale, and diverse dataset of artificial children's faces.
  • To provide a valuable resource for experimental research involving children's faces.
  • To enhance the diversity of age and ethnicity in facial image databases.

Main Methods:

  • Utilized deep neural networks to generate 500 synthetic, realistic children's face images.
  • Ensured diversity across ages (3-10 years) and 15 distinct ethnic groups.
  • Collected ratings from 585 adult participants to validate age, gender, ethnicity, and emotion perception.

Main Results:

  • The generated dataset comprises 500 diverse, artificial children's faces.
  • Adult participants successfully identified key attributes (age, gender, ethnicity, emotion) of the synthetic faces.
  • The dataset demonstrates representativeness across specified demographic variables.

Conclusions:

  • The novel dataset offers a significant advancement for research requiring children's facial imagery.
  • Public availability on Open Science Framework facilitates broader scientific access and utilization.
  • This resource can support studies in areas such as facial recognition, developmental studies, and AI bias mitigation.