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Full Length Article
Volume 2 , Issue 2, PP: 57-63 , 2020


Facial Expression Recognition with Gender Identification

Authors Names :   Shubham Gupta   1     Aarushi Dhawan   2     Arpit Gupta   3     Arun Kumar Dubey   4  

1  Affiliation :  Bharati Vidyapeeth's College of Engineering, INDIA

    Email :  shubhamgupta5111997@gmail.com

2  Affiliation :  Bharati Vidyapeeth's College of Engineering, INDIA

    Email :  aarushidhawan99@gmail.com

3  Affiliation :  Bharati Vidyapeeth's College of Engineering, INDIA

    Email :  guptaarpit09@yahoo.com

4  Affiliation :  Bharati Vidyapeeth's College of Engineering, INDIA

    Email :  arudubey@gmail.com

Doi   :  10.5281/zenodo.3944681

Received: March 12, 2020 Revised: April 19, 2020 Accepted: June 18, 2020

Abstract :

The human facial emotions recognition has attracted interest in the field of Artificial Intelligence. The emotions on a human face depicts what’s going on inside the mind. Facial expression recognition is the part of Facial recognition which is gaining more importance and need for it increases tremendously. Though there are methods to identify expressions using machine learning and Artificial Intelligence techniques, this work attempts to use convolution neural networks to recognize expressions and classify the expressions into 6 emotions categories. Various datasets are investigated and explored for training expression recognition models are explained in this paper and the models which are used in this paper are VGG 19 and RESSNET 18. We included facial emotional recognition with gender identification also. In this project we have used fer2013 and ck+ dataset and ultimately achieved 73% and 94% around accuracies respectively.

Keywords :

Facial Expression Recognition , Gender Identification

References :

[1] Ververidis, Dimitrios, Constantine Kotropoulos, and Ioannis Pitas. "Automatic emotional speech classification." 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 1. IEEE, 2004.


[2] Dubey, Arun Kumar, and Vanita Jain. "A review of face recognition methods using deep learning network." Journal of Information and Optimization Sciences 40.2 (2019): 547-558.


[3] Casale, Salvatore, et al. "Speech emotion classification using machine learning algorithms." 2008 IEEE international conference on semantic computing. IEEE, 2008.


[4] Clark, Elizabeth A., et al. "The Facial Action Coding System for Characterization of Human Affective Response to Consumer Product-Based Stimuli: A Systematic Review." Frontiers in Psychology 11 (2020).


[5] Yu, Zhiding, and Cha Zhang. "Image based static facial expression recognition with multiple deep network learning." Proceedings of the 2015 ACM on international conference on multimodal interaction. 2015.


[6] Aneja, Deepali, et al. "Modeling stylized character expressions via deep learning." Asian conference on computer vision. Springer, Cham, 2016.


[7] Ramachandran, Prajit, Barret Zoph, and Quoc V. Le. "Searching for activation functions." arXiv preprint arXiv:1710.05941 (2017).


[8] Goodfellow, Ian J., et al. "Challenges in representation learning: A report on three machine learning contests." International conference on neural information processing. Springer, Berlin, Heidelberg, 2013..


[9] ​Jain, Amit, Jeffrey Huang, and Shiaofen Fang. "Gender identification using frontal facial images." 2005 IEEE International Conference on Multimedia and Expo. IEEE, 2005..


[10]​ Tümen, Vedat, Ömer Faruk Söylemez, and Burhan Ergen. "Facial emotion recognition on a dataset using convolutional neural network." 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017.