Facial Emotion Recognition System (FERS&#...

Facial Emotion Recognition System (FERS) Using Machine Learning

Author Name : Pooja Pawar, Vaishnavi Ghosalkar, Eshwari Kedari, Dhanashri Kedari, Sarvesh Pawaskar

ABSTRACT

Face recognition has existed for a long time. Moving forward, employee emotion that is expressed on their face and experienced in their brain and recorded in video, electric signal or image form can be estimated. Human emotion recognition is urgently needed so that cutting edge artificial intelligence systems can mimic and predict facial reactions. Making educated decisions about the determination of purpose, the advertising of offerings, or security-related threats might benefit from this. While recognising emotions from photos or video is a simple operation for the human eye, it is extremely difficult for computers to do and necessitates the use of numerous image processing techniques for feature extraction. For this task, a variety of machine learning techniques are appropriate.

Machine learning algorithms must first be trained before being tested against an appropriate dataset for any detection or recognition. This study investigates a few feature extraction approaches and machine learning algorithms that might aid in the precise identification of human emotion. Facial Emotion Recognition System (FERS) has been proposed in this project to use machine learning to automatically identify employee emotions in real time. The machine learning model was trained using the dataset. By analysing the collected image, the FERS system is able to recognise six different emotions, including joy, sadness, surprise, fear, disgust, and rage. Results show that the predetermined goals have been met. The machine learning model was trained using the FER-2013 dataset. The Neural Networks and Support Vector Machine (SVM) are used to classify the facial emotions picture and helps to predict the correct image according to the target image.

Keywords: Facial expression recognition (FER), Local Binary pattern (LBP), Support Vector, Machine (SVM).