Seongmyeong Bun-i
A Daoist monk who reads physiognomy and palmistry
Analyze emotional consistency and regulation from neutral, smiling, and angry expression photos
Based on Paul Ekman's basic emotion theory and FACS (Facial Action Coding System), extracts emotions from facial expressions. Compares and synthesizes three expressions — neutral, smiling, angry — to three-dimensionally analyze emotional consistency and regulation ability.
Emotion Analysis is a modern analytical method that objectively extracts and interprets emotional states from a person's facial expressions. By comparing expressions in multiple situations — neutral, smiling, and angry — it assesses emotional consistency, regulation ability, and basic emotional tendencies.
Emotion Analysis is academically grounded in Paul Ekman's theory of basic emotions and the Facial Action Coding System (FACS). Ekman experimentally demonstrated that human emotions are universally expressed in facial expressions, which became the foundation of modern emotion science.
LunaWitch's Emotion Analysis takes three expression photos — neutral, smiling, and angry — extracts emotions from each, and compares and synthesizes them to analyze emotional consistency and regulation ability. It serves as reference for self-understanding and improving interpersonal relationships.
The scientific study of emotion began in the 19th century with Charles Darwin's 'The Expression of the Emotions in Man and Animals' (1872). Darwin argued that emotional expressions are products of evolutionary adaptation and that humans and animals share emotional expressions.
In the 20th century, psychologists began systematic study of emotion. In the 1960s, Silvan Tomkins proposed a theory classifying emotions as primary affects, which his students Paul Ekman and Carroll Izard developed. Ekman experimentally demonstrated that six basic emotions (happiness, sadness, anger, fear, disgust, surprise) are universally expressed in facial expressions.
In the 1970s, Ekman and Wallace Friesen developed the 'Facial Action Coding System (FACS)', which decomposes facial expressions into muscle units. It systematized the movements of facial muscles into 'Action Units (AUs)', providing the first tool for objectively measuring facial expressions. FACS was revised in 2002 and remains the standard in emotion research.
In the 21st century, the combination of computer vision and machine learning rapidly advanced emotion recognition technology. Emotion recognition APIs developed by companies such as Affectiva and Microsoft made it possible to extract seven emotions (happiness, sadness, anger, fear, disgust, surprise, neutral) from facial expressions in real time.
Paul Ekman (1934–) is an American psychologist and pioneer of emotion science who demonstrated the universality of emotions. In the 1960s, he conducted research among the Fore people of Papua New Guinea, confirming that the same six basic emotions appear in facial expressions even in cultures with entirely different backgrounds from Westerners.
The six basic emotions Ekman defined are happiness (Joy), sadness (Sadness), anger (Anger), fear (Fear), disgust (Disgust), and surprise (Surprise). These emotions are innate and universal, each expressed by an independent facial muscle pattern. Later, 'contempt' was added as a seventh basic emotion.
Ekman also distinguished 'complex emotions' beyond basic emotions. Emotions such as pride, shame, and guilt are derived from combinations of basic emotions or social contexts, and their expression may differ across cultures. This means that emotion analysis should distinguish basic from complex emotions in interpretation.
The Facial Action Coding System (FACS) is a facial expression measurement system published by Ekman and Friesen in 1978 that decomposes facial muscle movements into 'Action Units (AUs)'. For example, AU12 is the contraction of the zygomatic major that raises the mouth corners — the core action of a smile — and AU4 is the contraction of the corrugator that furrows the brow — the core action of displeasure.
FACS made it possible to record facial expressions as objective muscle data rather than subjective impressions. This enabled research distinguishing 'genuine' from 'fake' smiles: a genuine smile (Duchenne smile) involves both AU12 (zygomatic) and AU6 (orbicularis oculi), while a fake smile involves only AU12.
Modern emotion recognition technology automatically extracts Action Units through computer vision and classifies emotions. LunaWitch's Emotion Analysis is also based on this system, extracting Action Units from facial expressions and mapping them to basic emotions for analysis.
Emotional Consistency refers to how stable emotional expression remains across situations. If the emotional patterns extracted from neutral, smiling, and angry expressions are consistent, emotions are stable; if they vary greatly across situations, there is emotional fluctuation.
Emotion Regulation is the ability to appropriately manage and express emotions. According to James Gross's emotion regulation model, emotions are regulated through two methods: cognitive reappraisal and expressive suppression. Facial expression analysis allows indirect observation of these regulation patterns.
A small difference between neutral and smiling expressions suggests a natural positive tendency; a large difference may suggest a tendency to consciously express positivity. If anger appears strongly in the angry expression but recovers quickly, emotional expression is healthy; if anger persists, caution in emotion regulation may be needed.
Photo-based emotion analysis consists of detecting the face from a facial expression photo, extracting key landmarks, and inputting them into an emotion classification model to estimate emotions. Landmarks are coordinates of key facial regions such as eye corners, mouth corners, brow, and nose tip, and their relative positions and changes determine emotions.
LunaWitch's Emotion Analysis takes three expression photos — neutral, smiling, and angry. After extracting emotions from each photo, it compares the emotional change patterns across the three expressions to analyze emotional consistency and regulation ability. This enables more three-dimensional emotion analysis than single-expression analysis.
Results are organized as emotional consistency index, positive/negative emotion ratio, and emotion regulation patterns, synthesized to provide insight into individual emotional tendencies. All results are for reference and serve as an auxiliary tool for self-understanding and improving relationships.
Emotion analysis is used as a tool for self-understanding, improving interpersonal relationships, and mental management. Objectively understanding one's emotional tendencies allows setting directions for emotion regulation, and understanding others' emotional patterns improves empathy and communication.
In particular, emotional consistency and regulation ability can serve as reference indicators for stress management, leadership development, and teamwork improvement. A leader with stable emotions contributes to the team's psychological safety; a person with flexible emotion regulation is better positioned for constructive conflict resolution.
However, because emotion analysis is based on external expression (facial expression), it may not fully match inner emotions. Expressions can be consciously regulated. Therefore, emotion analysis results should be used as a starting point for self-reflection, combined with a process of introspection.
LunaWitch's Emotion Analysis is based on Paul Ekman's basic emotion theory and FACS (Facial Action Coding System), extracting emotions from three expression photos — neutral, smiling, and angry — and comparing and synthesizing them to analyze emotional consistency and regulation ability.
The academic achievements of emotion science are translated into modern language to provide practical insight for self-understanding and improving relationships. All results are for reference only, and we recommend using them as an auxiliary tool for self-reflection and better relationships.
Paul Ekman 'Emotions Revealed' (2003), Paul Ekman & Wallace Friesen 'Facial Action Coding System (FACS)' (1978, rev. 2002), Charles Darwin 'The Expression of the Emotions in Man and Animals' (1872), James Gross emotion regulation model (Stanford University), emotion science academic papers (APA·KCI)
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Emotion Analysis is a modern analytical method that objectively extracts and interprets emotional states from a person's facial expressions. By comparing expressions in multiple situations — neutral, smiling, and angry — it assesses emotional consistency, regulation ability, and basic emotional tendencies.
The scientific study of emotion began in the 19th century with Charles Darwin's 'The Expression of the Emotions in Man and Animals' (1872). Darwin argued that emotional expressions are products of evolutionary adaptation and that humans and animals share emotional expressions.
Paul Ekman (1934–) is an American psychologist and pioneer of emotion science who demonstrated the universality of emotions. In the 1960s, he conducted research among the Fore people of Papua New Guinea, confirming that the same six basic emotions appear in facial expressions even in cultures with entirely different backgrounds from Westerners.
Emotions, Seongmyeong Bun-i, Palmistry, Physiognomy, Dream Reading