Human face recognition to target commercial on digital display via gender

Abstract

Emotion recognition has been applied in many fields such as Medical, Security, and Business etc. There are many complications in evolving a good emotion recognition scheme for the human face in real time. Since most of the time facial features of expression and the style of presentation emotion to the outside world is dissimilar from person to person. Thus, it is very problematic to build a precise scheme for real time emotion recognition. This paper is to distinguish human facial expressions to predict the current emotional state. The system specially focused on reducing fatal road accidents due to drivers' state of emotion. Initially it is built to recognize the human emotion through facial expressions and then evaluated to detect drowsiness using facial landmarks to ensure the safety of the driver. Training has been done with Kaggle dataset for seven emotional states (Neutral, Happy, Angry, Sad, Scared, Surprised and Disgust) called universal emotions. In order to predict drowsiness, it uses specific twelve points on face (six points on each eye) in shape predictor sixty face landmarks. Evaluated system has given 71% accuracy in testing and drowsiness alert also showed a very good success rate.