Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Feedback System Using Facial Emotion Recognition

Authors
M. Nagaraju1, S. K. Vasim2, *, S. K. Mateen2, P. Giridhar2, T. Venkatram2
1Professor, Department of CSE, Vignan’s Lara Institute of Technology & Science, Vadlamudi, Chebrolu (Mandal), Guntur(D.T), Andhra Pradesh, India
2Final Year, DepartmentofCSE, Vignan’s Lara Institute of Technology & Science, Vadlamudi, Chebrolu (Mandal), Guntur(D.T), Andhra Pradesh, India
*Corresponding author. Email: shaikvasim000@gmail.com
Corresponding Author
S. K. Vasim
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_91How to use a DOI?
Keywords
Computer Vision; Deep Learning; Facial Emotions; Convolution Neural Networks; Emotion Analysis; OpenCV; tkinter
Abstract

Emotion plays a very crucial role for understanding what a person feels, As we enter into a digital era where people start to interact, learn and do various tasks by connecting through online mediums there is no physical interaction which helps us to understand the customer satisfaction. But when we are interacting with people online knowing their satisfaction for the service they provide has become a major challenge, this challenge can be faced by using the human emotions to extract their satisfaction level on the service being provided online. These emotions can be detected from the user’s using different AI/ML techniques and can be used as feedback to the service provider. Users choose between pre-recorded video files or live webcam feeds. The script detects faces in frames, extends regions to include more of the head, and extracts facial encodings. DeepFace is utilized to analyze dominant emotions. Visualizations including pie charts, histograms, and face images aid in interpreting emotional dynamics. The project facilitates sentiment analysis, audience engagement monitoring, and emotion-driven content creation across diverse fields. Its modular design supports easy extension and integration into larger systems for advanced analysis and applications.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
10.2991/978-94-6463-471-6_91
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_91How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M. Nagaraju
AU  - S. K. Vasim
AU  - S. K. Mateen
AU  - P. Giridhar
AU  - T. Venkatram
PY  - 2024
DA  - 2024/07/30
TI  - Feedback System Using Facial Emotion Recognition
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 955
EP  - 961
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_91
DO  - 10.2991/978-94-6463-471-6_91
ID  - Nagaraju2024
ER  -