MorphCast is the most comprehensive facial emotion recognition solution on the market thanks to more than 100 capabilities in facial expression recognition (FER).
Leveraging the renowned Circumplex Model of Affect developed by Russel, MorphCast offers a comprehensive and precise exploration of user emotional states. This model allows for a nuanced understanding of emotions, positioning them within a two-dimensional space, and our AI harnesses its depth to provide insights into the intricacies of an individual’s state of mind.
MorphCast features a compact yet powerful client-side AI engine capable of extracting the following facial data about an individual:
- Face detector: Detects the presence of a face in the field of view of the webcam or input image.
- Pose: Estimates the head pose rotation angles expressed in radians as pitch, roll, and yaw.
- Age: Estimates the likely age of the main face with a granularity of years, or within an age group for better numerical stability.
- Gender: Estimates the most likely gender of the main face, Male or Female.
- Emotions: Estimates the presence and the respective intensities of facial expressions in the format of seven core emotions – anger, disgust, fear, happiness, sadness, and surprise, plus the neutral expression – according to the Ekman discrete model.
- Arousal Valence: Estimates the emotional arousal and valence intensity. According to the dimensional model of Russell. Arousal is the degree of engagement (positive arousal), or disengagement (negative arousal); valence is the degree of pleasantness (positive valence), or unpleasantness (negative valence) completing the analysis with the probability of proximity to 98 different mental states: Adventurous, Afraid, Alarmed, Ambitious, Amorous, Amused, Angry, Annoyed, Anxious, Apathetic, Aroused, Ashamed, Astonished, At Ease, Attentive, Bellicose, Bitter, Bored, Calm, Compassionate, Conceited, Confident, Conscientious, Contemplative, Contemptuous, Content, Convinced, Courageous, Defiant, Dejected, Delighted, Depressed, Desperate, Despondent, Determined, Disappointed, Discontented, Disgusted, Dissatisfied, Distressed, Distrustful, Doubtful, Droopy, Embarrassed, Enraged, Enthusiastic, Envious, Excited, Expectant, Feel Guilt, Feel Well, Feeling Superior, Friendly, Frustrated, Glad, Gloomy, Happy, Hateful, Hesitant, Hopeful, Hostile, Impatient, Impressed, Indignant, Insulted, Interested , Jealous, Joyous, Languid, Light Hearted, Loathing, Longing, Lusting, Melancholic, Miserable, Passionate, Peaceful, Pensive, Pleased, Polite, Relaxed, Reverent, Sad, Satisfied, Selfconfident, Serene, Serious, Sleepy, Solemn, Startled, Suspicious, Taken Aback, Tense, Tired, Triumphant, Uncomfortable, Wavering, Worried.
- Attention: Estimates the attention level of the user to the screen, considering whether the user’s face is in or out of the field of view of the webcam, head position and other emotional and mood behavior.
- Wish: Estimates the value of the MorphCast® Face Wish index. This is a proprietary metric that, considering the interest and sentiment of a customer, summarizes in a holistic manner his/her experience about a particular content or product presented on the screen.
- Positivity: Gauges the intensity of arousal and valence based on the 17-degree angle of the circumflex model of affects (Russel). This exclusive metric provides a comprehensive overview of an individual’s positivity, capturing facial expressions.
- Alarms: Several alarm are outputing by the AI engine to help developer to trigger reactions at possible cheating situations (NO FACE, MORE FACES, LOW ATTENTION…).
- Other Features: Estimates the presence of the following face features: Arched Eyebrows, Double Chin, Narrow Eyes, Attractive, Earrings, Necklace, Bags Under Eyes, Eyebrows Bushy, Necktie, Bald, Eyeglasses, No Beard, Bangs, Goatee, Oval Face, Beard 5 O’Clock Shadow, Gray Hair, Pale Skin, Big Lips, Hat, Pointy Nose, Big Nose, Heavy Makeup, Receding Hairline, Black Hair, High Cheekbones, Rosy Cheeks, Blond Hair, Lipstick, Sideburns, Brown Hair, Mouth Slightly Open, Straight Hair, Chubby, Mustache, Wavy Hair.
- Russell, J., Lewicka, M. & Niit, T. (1989). A cross-cultural study of a circumplex model of affect. Journal of personality and social psychology, 57, 848–856.
- Scherer, Klaus. (2005). Scherer KR. What are emotions? And how can they be measured? Soc Sci Inf 44: 695-729. Social Science Information. 44. 695-792.
- Ahn, Junghyun & Gobron, Stéphane & Silvestre, Quentin & Thalmann, Daniel. (2010). Asymmetrical Facial Expressions based on an Advanced Interpretation of Two-dimensional Russells Emotional Model.
- Paltoglou, G., & Thelwall, M. (2012). Seeing stars of valence and arousal in blog posts. IEEE Transactions on Affective Computing, 4(1), 116-123.
- Paul Ekman Basic-Emotions