Research Article
Deep Learning Based Hybrid Approach For Facial Emotion Detection
@INPROCEEDINGS{10.4108/eai.7-12-2021.2314585, author={SURIYA Sundaramoorthy and Babuvignesh C}, title={Deep Learning Based Hybrid Approach For Facial Emotion Detection}, proceedings={Proceedings of the First International Conference on Combinatorial and Optimization, ICCAP 2021, December 7-8 2021, Chennai, India}, publisher={EAI}, proceedings_a={ICCAP}, year={2021}, month={12}, keywords={motion recognition facedetection haar cascade deep learning cnn and svm computer vision image processing}, doi={10.4108/eai.7-12-2021.2314585} }
- SURIYA Sundaramoorthy
Babuvignesh C
Year: 2021
Deep Learning Based Hybrid Approach For Facial Emotion Detection
ICCAP
EAI
DOI: 10.4108/eai.7-12-2021.2314585
Abstract
Humans exhibit an essential set of feelings which might be exhibited via steady facial expressions. Emotions have an important role in teaching as well as other disciplines. It is understood that, while culture, the environment, the language and behavior of people vary, emotions are considered to be universal among the entire human population. Emotions are also important in the realm of education, because their power rivals that of the environment or the language used to communicate information. It's important for cognitive functions including learning and digesting new information.Student emotions during lectures play an important role whether it's in classrooms or in virtual learning environments. Unfortunately, due to the adoption of a virtual method of study or simply the incapacity of humans to keep track of all students in a classroom, teachers do not always keep students' emotions in check, making it difficult to adjust and keep the line of communication open.Thus automated facial emotion detection is very useful and brings the hidden indicators of students internal emotions to limelight. The suggested method aids in the detection of emotions and their classification in order to detect interest in a topic, which is then used as feedback to the course management staff in order to improve learner experience and aid in course material updates.