📄 Abstract
Face detection has been around for ages. The main objective of face recognition is to authenticate and identify the countenance. Taking a step forward, human emotion detection is the need of the hour so that modern artificial intelligent systems can get reactions from face. Facial emotion detection can be used to understand the human behavior, detection of mental disorders and synthetic human expressions. This can be done by using machine learning algorithms used in facial recognition for accurate identification and detection. However, the countenance are captured in Realtime and processed using hear cascade detection. The project work is defined in three different phases where within the first phase, Face is detected from the camera and within the second phase, the captured input is analyzed using the features with support of keras convolutional neural network model. Within the last phase, Face is authenticated to classify the emotions of human as happy, neutral, angry, sad, disgust, fear and surprise. The proposed work presented is simplified in three phases such as detection of face, recognition and classification of emotion. In this project Open CV library, Keras, Tensorflow, Pandas, Numpy, Dataset, Jupyter Notebook and Python Programming is used.
🏷️ Keywords
📚 How to Cite:
Dr.V.Vijayakumar, R.Surendhar , REALTIME FACIAL EMOTION RECOGNITION SYSTEM , Volume 10 , Issue 7, july 2025, EPRA International Journal of Research & Development (IJRD) ,