Emotion recognition
Best-in-class machine learning algorithms to accurately measuring the expression of emotions.
Proprietary Machine Learning algorithms
We have developed specific machine learning algorithms instead of deep learning. The most relevant motivation is due to the transparency, the ability to have control and knowledge of all the processes to achieve the best results.
Action Units
Specific classification based on action units.
Face geometry
Face's geometries detection to determine the human presence.
Appearence
Face geometry detection to determine its presence.
Relations
Strong correlation between all action units for better accuracy.
Beyond the six primary emotions
Machine learning algorithms measure Action Units with high precision to analyze complex emotional states and investigate other parameters such as emotional engagement and attention.
Attention
With the attention, you will have information related to cognitive-behavioural activation.
Arousal
It allows understanding the intensity by which emotions are revealing.
valence
It is possible to determine whether the emotions felt have a positive or negative value.
APPLICATION PROGRAMMING INTERFACE
We collect emotions.
You receive data
You receive data
Seamless integration
Using this API service, it is possible to use our best-in-class emotion recognition technology in real-time, in any application field.
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