Human Emotion Detection to Emoji Display Using Machine Learning

In Human body facial muscle consumes 70% of energy to make expressions against various emotions. Most importantly face has around 42 striated muscles and 14 facial bones all together perform an important function in the daily life cycle. Facial emotions can be replaced by Emoji reactions for example Sadness, Contempt, Surprise, Anger, Fear, and Happiness, among Humans are able to recognise facial expressions with ease, but computers struggle to do the same. In some circumstances, recent techniques have offered AI technology for facial skeleton marking to generate apps and avatars. This paper explains technologies developed for automatic facial reaction captured through 5.0 MP Pi Digicam is interfaced with Raspberry pi in CSI (Camera Serial Interface) using IDLE Python 3.11.2. Here Raspberry pi OS is used to get display photographs clearly as it works faster than the existing model and it is widely used in wireless printing servers, controllers of the robot, and Standard tripod stop motion cameras. This paper reflects in the below applications: Lie detections used by crime branch departments, In Hospitals to monitor intensive care patients. This model will support for several domains such as Hospitals and Anti-crime Units. This output will be monitored by 24/7 for tracking purposes and provide a detailed Data log sheet with emoji’s.