Facial Emotion Based Face Emoji Generation

Authors

  • Manukonda Raj Kumar PG scholar, Department of MCA, CDNR collage, Bhimavaram, Andhra Pradesh. Author
  • A.Durga Devi (Assistant Professor), Master of Computer Applications, DNR collage, Bhimavaram, Andhra Pradesh. Author

Keywords:

Emoticons, Human-Computer Interaction, Facial Expression Recognition, Machine Learning, Deep learning.

Abstract

Face expressions are an intrinsic aspect of
nonverbal communication and play a significant role
in Human Computer Interaction. The formation of
facial emoticons is a human-computer interaction
device. Emoji generation in real time based on a
person's facial expression hasalways been difficult.
Human social conversations depend on facial
expressions. Since the world is becoming more
technologically sophisticated day in day out, there
are more interactive encounters, such as text
messages, than physical ones. Emoticons promote
virtual social interaction by reducing the amount of
words exchanged. This paper describes an Emoji
generation methodology based on Facial Expression
Recognition (FER) and Convolutional Neural
Networks (CNN) coupled with Machine Learning
and Deep Learning. This CNN-based model can be
put to work to evaluate feelings as users watch movie
trailers or video lessons, as well as to help people with
autism regulate their emotions.

Downloads

Download data is not yet available.

References

Alshamsi, Humaid, Veton Kepuska, and Hongying Meng.

"Real time automated facial expression recognition app

development on smart phones." In 2017 8th IEEE Annual

Information Technology, Electronics and Mobile

Communication Conference (IEMCON), pp. 384-392. IEEE,

2017.

[2] Ekman .P & Keltner, D Universal facial expressions of

emotion: An old controversy and new findings. In U. C.

Segerstråle & P. Molnár (Eds.), Nonverbal communication:

Where nature meets culture (pp. 27–46). Lawrence Erlbaum

Associates, Inc. 1997.

[3] Fathallah, Abir, Lotfi Abdi, and Ali Douik. "Facial

expression recognition via deep learning." In 2017 IEEE/ACS

14th International Conference on Computer Systems and

Applications (AICCSA), pp. 745-750. IEEE, 2017.

[4] Goodfellow, Ian J., Yaroslav Bulatov, Julian Ibarz, Sacha

Arnoud, and Vinay Shet. "Multi-digit number recognition from

street view imagery using deep convolutional neural networks."

arXiv preprint arXiv:1312.6082, 2013.

[5] McDuff, D., Mahmoud, A., Mavadati, M., Amr, M., Turcot,

J., & Kaliouby, R. E. (2016, May). AFFDEX SDK: a crossplatform

realtime multi-face expression recognition toolkit. In

Proceedings of the CHI conference extended abstracts on human

factors in computing systems (pp. 3723-3726). ACM, 2016.

[6] J. Chen, Y. Lv, R. Xu, and C. Xu, "Automatic social signal

analysis: Facial expression recognition using difference

convolution neural network," Journal of Parallel and Distributed

Computing, vol. 131, pp. 97-102, 2019.

[7] Barsoum, Emad, et al, Training deep networks for facial

expression recognition with crowdsourced label distribution,

ACM International Conference on Multimodal Interaction

ACM, pp. 279—283, 2016.

[8] Martinez, Brais, et al, Automatic analysis of facial actions: A

survey, IEEE Transactions on Affective Computing, 2017.

[9] H.-D. Nguyen, S. Yeom, G.-S. Lee, H.-J. Yang, I. Na, and S.

H. Kim, "Facial Emotion Recognition Using an Ensemble of

MultiLevel Convolutional Neural Networks," International

Journal of Pattern Recognition and Artificial Intelligence, 2018.

[10] T. Cao and M. Li, "Facial Expression Recognition

Algorithm Based on the Combination of CNN and K-Means,"

presented at the Proceedings of the 2019 11th International

Conference on Machine Learning and Computing, Zhuhai,

China, 2019.

[11] N. Christou and N. Kanojiya, "Human Facial Expression

Recognition with Convolutional Neural Networks," Singapore,

2019, pp. 539-545: Springer Singapore

[12] A. Sajjanhar, Z. Wu, and Q. Wen, "Deep learning models

for facial expression recognition," in 2018 Digital Image

Computing: Techniques and Applications (DICTA), 2018, pp.

1-6: I EEE.

[13] J. Chen, Y. Lv, R. Xu, and C. Xu, "Automatic social signal

analysis: Facial expression recognition using difference

convolution neural network," Journal of Parallel and Distributed

Computing, vol. 131, pp. 97-102, 2019.

[14]Al-Sumaidaee, Saadoon AM, et al, Multi-gradient features

and elongated quinary pattern encoding for image-based facial

expression recognition, Pattern Recognition, 2017, pp. 249—

263.

[15] Barsoum, Emad, et al, Training deep networks for facial

expression recognition with crowd-sourced label distribution,

ACM International Conference on Multimodal Interaction

ACM, 2016, pp. 279—283.

Downloads

Published

2025-05-01

Issue

Section

Articles

How to Cite

Facial Emotion Based Face Emoji Generation. (2025). International Journal of Multidisciplinary Engineering In Current Research, 10(5), 77-84. https://ijmec.com/index.php/multidisciplinary/article/view/620

Most read articles by the same author(s)

1 2 > >>