Lately we hear a lot about Facial Emotion Recognition, but what exactly is it all about?
Facial emotions and their analysis play an essential role in the non-verbal communication. In particular, they enhance oral communication and boost the ability to understand concepts. No matter what gender, culture, or ethnicity, most people are capable of recognizing emotions expressed by the human face.
Nevertheless, the automation of this process is a relatively recent development. Artificial Intelligence has made many strides in recent years. There are now technological solutions that can detect, analyze and recognize emotional states by analyzing facial expressions.
What is Facial Emotion Recognition tech?
Facial Emotion Recognition is a technology able to detect facial expressions of people. It does it by analyzing images or videos and determining the emotional state from the detected expression. Indeed, it is a subset of what is called Emotion AI or Affective Computing, a multidisciplinary tech field that uses Artificial Intelligence to recognize and interpret human emotions.
But how does Facial Emotion Recognition work? Basically, in order to teach AI to recognize human emotions, it is necessary to train it to detect a face, recognize the expression, and relate it to an emotion. There are different models of emotion classification. From Paul Ekman’s 6 basic emotions model to Russel, Scherer and Klaus’ circumplex model of affect, which identifies 98 mental states of mind. So, based on the psychological and scientific model used to train the AI, the emotion recognition can be more or less deep.
Obviously, Facial Emotion Recognition technologies cannot read people’s minds! What they can detect is “apparent” emotion, based on the expression under analysis. And of course, they are generally more accurate in recognizing spontaneous, rather than posed, expressions.
How can it be used?
Facial Expression Recognition technologies can cover a wide range of applications. It is a cross-cutting technology that can be used where emotion recognition can bring value in terms of increasing user engagement or solution effectiveness.
Below are some examples, which are certainly not exhaustive, of uses of Facial Emotion Recognition:
- Education and training. By determining the emotional states of learners, it is possible to adapt the learning path on each single user. It is also possible to determine their attention level and engagement and use these data to make the training sessions more effective.
- Human resources. Facial Emotion Recognition provides recruiters with objective and scientific data on emotional reaction of candidates during job interviews. Also, it allows to measure the mood and engagement of employees during training sessions, meetings, and much more.
- Digital advertising. The possibility of detecting and recognizing the emotional states and reactions of customers, makes advertisers able to personalize the communication with online users. This allows to boost their engagement and increase the efficacy of marketing investments.
- Retail and digital signage. Emotion Recognition allows to tailor the communication by displaying personalized messages or products for each single viewer.
- Entertainment. By detecting the emotion and mood of users, it is possible to personalize contents, predict reactions to specific contents, and provide contextual and customized recommendations.