Human Computer Interface Application for Emotion Detection Using Facial Recognition

An essential tool for describing human emotion is facial expression. From morning tonight, people go through a broad spectrum of emotions that may be caused by their mental or physical health. The six major facial expressions of happy, sorrow, surprise, fear, disgust, and rage are now classified by psychology as six universal emotions, despite the fact that humans experience a broad variety of emotions. Facial muscle movements may be used to determine humane motions. The brow, lips, nose, and eyes are the four primary facial characteristics Facial recognition is a topic that is now the focus of much investigation. Finding a match between the input image and the images to red in the database is the aim of face recognition. Human- computer interaction and the solution to the problem of criminal identification depend on facial recognition. The data in face recognition tasks has a high intrinsic complexity, making the dimensionality reduction strategy essential. Picture space's dimensionality is decreased using PCA. In the domains of computer vision, image processing, pattern recognition and other areas, the modelling of the face using Gabor features has generated a lot of attention. The major justification for using the Gabor filter is its biological significance. Mammal primary visual cortex neurons have an accessible field profile that is oriented toward spatial frequency features. Additionally, Gabor filters may make advantage of well-known visual properties as spatial localization, orientation selectivity and spatial frequency feature. So, we are proposing this computational model approach for the detection of emotional changes using dataset from EMOTIC database by recognition system. In this approach we achieved around 88% accuracy which efficient and better when it's been compared with computer modeling Methodologies.