Facial Expression Recognition Based Recommendation System

  • S. Iniyan, Vaibhav Gupta, Samarth Gupta


     With advancements in today’s deep learning techniques, one of the important and challenging task in human – computer interaction is Facial Expression Recognition. Real time detection of face and interpreting different facial expressions like happy, anger, disgust, sad, fear, surprise etc. is based on facial features and their actions. Characteristics were used for six topics, coefficients which describe elements of facial expressions. The techniques used in FER  consists of three steps - preprocessing, extraction of feature and classification. The algorithm of system uses Convolutional Neural Network (CNN)  to extract features from the face image and further Artificial Neural Network is used. The extracted features are given to the classifier which predicts the recognized expression as output. Using this output expression, the content is recommended to the user based on their real time mood. The Model will be robust with a high precision and straightforward addition of attributes from various sources to the set.

How to Cite
Samarth Gupta, S. I. V. G. (2020). Facial Expression Recognition Based Recommendation System. International Journal of Advanced Science and Technology, 29(3), 5669 - 5678. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/6192