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Related Concept Videos

Physiology of Emotion01:20

Physiology of Emotion

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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...
952
Labeling Emotion01:20

Labeling Emotion

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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...
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Facial Feedback Hypothesis01:24

Facial Feedback Hypothesis

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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...
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Cognitive Theories: Schachter-Singer Theory of Emotion01:20

Cognitive Theories: Schachter-Singer Theory of Emotion

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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...
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Emotional Expression01:26

Emotional Expression

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Emotional expression encompasses how individuals convey their emotions through verbal communication and non-verbal cues. These non-verbal actions include facial expressions, body language, and physical gestures, such as frowning or smiling. Among these, facial expressions play a crucial role in emotional expression and are understood universally, indicating a biological basis for how humans communicate emotions.
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...
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Physiological Theories: James-Lange Theory of Emotion01:16

Physiological Theories: James-Lange Theory of Emotion

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The James-Lange theory of emotion, proposed by William James and Carl Lange in the late 19th century, asserts that emotions are the result of physiological reactions to external stimuli. Contrary to the traditional view, which suggests that emotions directly arise from the perception of stimuli, this theory proposes that emotions occur as a consequence of the body's responses to such stimuli. According to this framework, an emotional experience is a cognitive interpretation of physiological...
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New Trends in Emotion Recognition Using Image Analysis by Neural Networks, A Systematic Review.

Andrada-Livia Cîrneanu1, Dan Popescu1, Dragoș Iordache2

  • 1Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.

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Facial emotion recognition (FER) systems use deep neural networks for accurate human expression analysis. This review highlights convolutional neural networks (CNNs) as key for advancing FER applications in various fields.

Keywords:
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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Machine Learning

Background:

  • Facial emotion recognition (FER) is crucial for applications in education, healthcare, and public safety.
  • Deep neural networks (DNNs) offer advanced feature extraction and computational efficiency for image analysis tasks like FER.
  • Accurate detection and recognition of human emotional expressions are paramount for effective FER system deployment.

Conclusions:

  • CNN-based architectures show significant promise for advancing FER.
  • FER systems have diverse applications in healthcare, education, security, and social IoT.
  • Future research should address open issues and explore new developments in FER technology.