Emotion detection using FCM for controlling devices
- DOI
- 10.2991/978-94-6463-250-7_4How to use a DOI?
- Keywords
- Neural Networks; Machine Learning; Fuzzy C-Means; WLD; Convolutional Neural Networks
- Abstract
The human face is the most important and significant bodily part that contributes greatly to both human to human and human to machine communication. We always recognize a person by their face, from which we can infer their gender, extrapolate their age, and also deduce certain cultural traits. The technology we use most frequently today is face detection, and a number of programmes need to be able to recognize emotions. The prevalent models do not use feelings to regulate device operation; instead, they rely on facial function identification from a whole image, which has a low accuracy level. The suggested module gathers photos from a camera or a database, recognizes faces, and then extracts features in order to build a powerful emotion detection tool for practical applications. Fuzzy clustering is used to identify different human emotions including happiness, sadness, and fear while managing the technology. These robust devices are made to be employed in successful human-computer interaction and human decision-making.
- 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
TY - CONF AU - G. Dhanalakshmi AU - S. Pratheebha AU - R. L. Thanappriya AU - N. S. Monika PY - 2023 DA - 2023/10/17 TI - Emotion detection using FCM for controlling devices BT - Proceedings of the 6th International Conference on Intelligent Computing (ICIC-6 2023) PB - Atlantis Press SP - 15 EP - 19 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-250-7_4 DO - 10.2991/978-94-6463-250-7_4 ID - Dhanalakshmi2023 ER -