“Emotion recognition” means using artificial intelligence (AI) to read facial expressions and other non-verbal cues to figure out how happy a customer is with a service or product. Employing emotion recognition software technology, the software may “analyze” a human face’s emotions using sophisticated picture dispensing. It is common to use cameras with face detection software to record people’s reactions in real-time and then look at their faces to figure out what they were thinking. Each demeanor causes facial muscles to flex and relax differently, which helps AI algorithms determine emotion.
How do we distinguish basic emotions?
There are seven recognized emotions, each with a corresponding list of facial cues. Deep learning and emotion recognition algorithms use massive amounts of images as training data to pick up on these quirks.
- Signs of happiness include an arching brow and a crinkled grin.
- Surprise – Eyebrows lifted, upper eyelids elevated, jaw dropped
- Anger – Lowered eyebrows, wide eyes, and a tight drooping lip
- Open mouth, horizontally compressed lips, and puffed-out upper eyelids are all signs of fear.
- Sadness is a furrowed smile featuring pulled-down lips corners and drooping eyelids.
- Displaying distaste involves making a “u” with the upper lip, lowering the eyebrows, and making a “w” shape with the nose.
- Contempt – Prominent lip edge along one face side that might be paired with a smiling or angry expression.
A deep learning-based emotion analysis product, MorphCast can detect seven common emotions without revealing the user’s identity and in real-time. As a result of its training on several data sets, it can analyze facial expressions with greater precision. When an emotion is identified, a confidence score and timestamp are provided, and the collected data can be viewed in a centralized location using any available data visualization dashboard.
Why is it beneficial to use emotion recognition software?
Though emotion detection via technology was considered a formidable challenge, recent advances in deep learning have shown encouraging results. By employing emotion recognition software, businesses may scan photos and recordings in real-time to monitor camera feeds or automate video analytics, saving money and improving user experience. We at MorphCast have integrated the study of human expressions with AI to develop a system that can automatically identify a wide range of universal emotions based on a person’s facial expressions. Up to seven distinct moods can be detected in real-time by our face analysis program, all while maintaining complete anonymity for each user.