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

Cognitive Theories: Schachter-Singer Theory of Emotion01:20

Cognitive Theories: Schachter-Singer Theory of Emotion

2.2K
Stanley Schachter and Jerome Singer proposed the two-factor theory of emotion, which emphasizes the interplay between physiological arousal and cognitive labeling in forming emotional experiences. This theory suggests that emotions are not simply a result of physiological responses but rather a combination of these responses and the individual's cognitive interpretation of them.
Physiological Arousal and Cognitive Labeling
According to this theory, when an individual experiences...
2.2K
Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

802
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...
802
Labeling Emotion01:20

Labeling Emotion

860
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
860
Physiological Theories: Cannon-Bard Theory of Emotion01:22

Physiological Theories: Cannon-Bard Theory of Emotion

2.0K
The Cannon-Bard theory of emotion, proposed by Walter Cannon and Philip Bard, challenges the notion that emotions are solely the result of physiological responses. Instead, this theory suggests that emotional experiences and physiological arousal occur simultaneously but operate through independent mechanisms. This dual response is initiated by the brain, specifically by the thalamus, which plays a critical role in processing sensory information.
Upon perceiving a stimulus, such as a dangerous...
2.0K
Cognitive Theories: Lazarus Mediational Theory of Emotion01:17

Cognitive Theories: Lazarus Mediational Theory of Emotion

2.5K
Richard Lazarus' cognitive mediational theory highlights the pivotal role of cognitive appraisal in shaping emotional responses. According to this theory, the evaluation of a stimulus — based on personal values, goals, beliefs, and expectations — mediates the emotional response. This appraisal process is immediate and often occurs unconsciously, influencing the intensity and nature of the resulting emotion.
Cognitive Appraisal and Emotional Response
Lazarus proposed that...
2.5K
Physiology of Emotion01:20

Physiology of Emotion

4.1K
The physiology of emotions is a multifaceted process involving the autonomic nervous system, brain structures, hormones, and neurotransmitters. This intricate interplay dictates how emotions manifest in the body and influence behavior.
Autonomic Nervous System
The autonomic nervous system (ANS) plays a critical role in emotional responses by regulating involuntary physiological functions. It consists of two main components: the sympathetic and parasympathetic systems. The sympathetic system...
4.1K

You might also read

Related Articles

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

Sort by
Same author

Comparison of Outcomes and Radiation Exposure using Fiber-Optic RealShape enabled standard guidewire (FORS) vs. LumiGuide for Fenestrated-Branched Endovascular Aortic Aneurysm Repair.

Journal of vascular surgery·2026
Same author

A Sulfonamide-Based Compound DRZ-V Enhances Wound Repair via Macrophage-Mediated Responses Associated with TIRAP-NF-κB Signaling.

Pharmaceutical research·2026
Same author

Adaptor proteins regulating tumor-associated macrophage polarization during cancer progression.

Oncoscience·2026
Same author

Modulating IL-1β-induced pro-atherogenic endothelial responses through drug repurposing.

Inflammopharmacology·2026
Same author

Dual action of herbal compounds in <i>Klebsiella pneumoniae</i> infection and associated inflammatory diseases.

Frontiers in immunology·2026
Same author

CAR-T/NK/M-based combination therapies in cancer: A comprehensive review.

Current problems in cancer·2026
Same journal

AI-driven neuroanalytic modeling for mental health: multichannel CNN-based autism spectrum disorder detection via facial pattern analysis.

Frontiers in computational neuroscience·2026
Same journal

Modeling multiscale neural dynamics for EEG-based emotion recognition using an attentive wavelet-transformer framework.

Frontiers in computational neuroscience·2026
Same journal

New directions for complex systems in contemporary neuroscience: a morphodynamic and emergent function approach.

Frontiers in computational neuroscience·2026
Same journal

NMDA receptor kinetics drive distinct routes to chaotic firing in pyramidal neurons.

Frontiers in computational neuroscience·2026
Same journal

Schumann-anchored golden ratio organization of human neural oscillations.

Frontiers in computational neuroscience·2026
Same journal

Toward model-guided electrophysiology-Encoding of chirps in the electrosensory periphery of <i>Apteronotus leptorhynchus</i>.

Frontiers in computational neuroscience·2026
See all related articles

Related Experiment Video

Updated: Mar 17, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.6K

A Hierarchical Bayesian Model for Crowd Emotions.

Oscar J Urizar1, Mirza S Baig2, Emilia I Barakova1

  • 1Department of Industrial Design, Eindhoven University of Technology Eindhoven, Netherlands.

Frontiers in Computational Neuroscience
|July 27, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel hierarchical Bayesian model for unsupervised emotion estimation in crowds. The model accurately infers individual and crowd emotional states by analyzing behavior patterns, achieving high accuracy.

Keywords:
crowd behavioremotion estimation in crowdsestimation of individual and collective emotions

More Related Videos

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.9K
Measuring Attentional Biases for Threat in Children and Adults
08:25

Measuring Attentional Biases for Threat in Children and Adults

Published on: October 19, 2014

15.9K

Related Experiment Videos

Last Updated: Mar 17, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

5.6K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.9K
Measuring Attentional Biases for Threat in Children and Adults
08:25

Measuring Attentional Biases for Threat in Children and Adults

Published on: October 19, 2014

15.9K

Area of Science:

  • Artificial Intelligence
  • Computer Vision
  • Behavioral Science

Background:

  • Emotion estimation in crowded environments is crucial for intelligent systems but remains challenging due to complex human emotional expression and perception limitations.
  • Existing methods struggle with the nuanced manifestation of emotions within group dynamics.

Purpose of the Study:

  • To develop an unsupervised hierarchical Bayesian model for inferring individual and crowd emotional states.
  • To explore the relationship between observed behaviors and emotional states in simulated crowded environments.
  • To enhance the capabilities of intelligent systems in perceiving and analyzing emotions in crowds.

Main Methods:

  • Utilized a self-organizing map to represent individual motion patterns.
  • Employed a hierarchical Bayesian network to build probabilistic models for behavior identification.
  • Developed unsupervised learning to infer emotional states of individuals and the crowd as a collective entity.

Main Results:

  • Achieved 74% accuracy in individual emotion estimation.
  • Reached 81% accuracy in crowd emotion estimation.
  • Demonstrated comparable performance to existing pedestrian behavior detection methods while introducing novel crowd analysis concepts.

Conclusions:

  • The proposed hierarchical Bayesian model effectively learns and infers emotional states in individuals and crowds.
  • The method provides a robust approach for analyzing group dynamics and emotional expression in complex environments.
  • This research advances the field of intelligent systems for emotion recognition in crowded settings.