vithika-karan/Face-Emotion-Recognition

E-learning is a network-enabled transfer of skills and knowledge in which education is delivered to a large number of people at the same time or at different periods. This makes it highly difficult for the teachers to understand whether the student is able to grasp the concepts or not. Here comes the role of Facial Emotion Recognition. It is an application of computer vision tasks to predict emotions on the basis of facial landmarks and gestural changes. The approach followed here is to explore the FER2013 dataset, preprocess it, use data augmentation techniques in order to get more generalized results and train a CNN model to finally get a real time emotion detector which can be used in the above business problem of the web based industries to get more motivated and focused students.

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Experimental

This project helps e-learning instructors understand student engagement during live online classes. By analyzing video feeds of students' faces, it identifies emotions like happy, sad, or neutral in real-time. This provides instructors with immediate feedback on how well students are grasping the material, allowing them to adjust their teaching pace or offer targeted support. This tool is designed for online educators and e-learning platform administrators.

No commits in the last 6 months.

Use this if you are an online educator or an e-learning platform looking to monitor student emotional responses and engagement during live virtual classes.

Not ideal if you need highly accurate, nuanced emotion detection for individual students in very diverse or low-light environments, or if privacy concerns prohibit real-time facial analysis.

e-learning online-education student-engagement classroom-monitoring instructor-feedback
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 8 / 25

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Stars

8

Forks

1

Language

Jupyter Notebook

License

MIT

Last pushed

May 29, 2022

Commits (30d)

0

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