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2020 | OriginalPaper | Chapter

Facial Expression Recognition for Human Computer Interaction

Authors : Joyati Chattopadhyay, Souvik Kundu, Arpita Chakraborty, Jyoti Sekhar Banerjee

Published in: New Trends in Computational Vision and Bio-inspired Computing

Publisher: Springer International Publishing

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Abstract

Facial expressions consisting of various emotions play a significant role in interpersonal relations. Emotion detection from various expressions of the face can be performed broadly in three major steps which involve face detection-normalization, extraction of features and classification. An automated facial expression detection methodology has been introduced by the authors in this letter. Here, after face detection and normalization we extract three different types of facial features: Geometric, Texture and Structural. Based on these extracted features we employ SVM classifier to separate the face expressions which includes Happy, Sad, Disgust, Angry, Surprise and Fear. We have applied our algorithm on two databases: JAFFE and COHEN. We have successfully detected over 80% expressions from JAFFE and COHEN database.

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Banerjee, J., Maiti, S., Chakraborty, S., Dutta, S., Chakraborty, A., Banerjee, J.S., “Impact of machine learning in various network security applications.” In Proc. ICCMC 2019 (press), IEEE, (2019).

Cheng Lin, K., Huang, T. C., Hung, J. C., Yen, N. Y., Ju Chen, S.: Facial emotion recognition towards affective computing-based learning. Library Hi Tech, 31(2), 294–307. (2013)

Chakraborty, A., Banerjee, J.S.: Effects of different digital modulation schemes for image transmission through wireless fading channels, LAP Lambert Academic Publishing (2017)

Banerjee, J. S., Chakraborty, A., & Chattopadhyay, A.: Reliable best-relay selection for secondary transmission in co-operation based cognitive radio systems: A multi-criteria approach. Journal of Mechanics of Continua and Mathematical Sciences, 13(2), 24–42, (2018).

Banerjee, J. S., Chakraborty, A., & Chattopadhyay, A.: A novel best relay selection protocol for cooperative cognitive radio systems using fuzzy AHP. Journal of Mechanics of Continua and Mathematical Sciences, 13(2), 72–87, (2018).

Chakraborty, A., Banerjee, J. S., & Chattopadhyay, A.: Non-uniform quantized data fusion rule for data rate saving and reducing control channel overhead for cooperative spectrum sensing in cognitive radio networks. Wireless Personal Communications, 104(2), 837–851, (2019).

Saha, O., Chakraborty, A., & Banerjee, J. S.: A fuzzy AHP approach to IT-based stream selection for admission in technical institutions in India. In Emerging Technologies in Data Mining and Information Security (pp. 847–858). Springer, Singapore, (2019).

Pandey, I., Dutta, H. S., and Banerjee, J.S.: WBAN: A Smart Approach to Next Generation e-healthcare System. In Proc. ICCMC 2019 (press), IEEE, (2019).

Paul, S., Chakraborty, A., & Banerjee, J. S.: The extent analysis based fuzzy AHP approach for relay selection in WBAN. In Cognitive Informatics and Soft Computing (pp. 331–341). Springer, Singapore, (2019).

10.

Paul, S., Chakraborty, A., & Banerjee, J. S.: A fuzzy AHP-Based relay node selection protocol for wireless body area networks (WBAN). In 2017 4th International Conference on Opto-Electronics and Applied Optics (Optronix), pp. 1–6. IEEE (2017, November).

11.

Mollahosseini, A., Chan, D., & Mahoor, M. H.: Going deeper in facial expression recognition using deep neural networks. In Applications of Computer Vision (WACV), 2016 IEEE Winter Conference on (pp. 1–10). IEEE (2016)

12.

Chérifa, Z., & Nasr Eddine, B.: Facial Expressions Recognition: Development and Application to HMI. In Computational Intelligence and Its Applications: 6th IFIP TC 5 International Conference, CIIA 2018, Oran, Algeria, May 8–10, 2018, Proceedings 6 (pp. 573–584). Springer International Publishing (2018)

13.

Khan Rizwan A., Meyer A., Konik, H. and Bouakaz, S.: Saliency-based framework for facial expression recognition. Frontiers of Computer Science, pp. 1–16, (2018)

14.

Ekman, P.: An argument for basic emotions. Cognition & emotion, 6(3–4), 169–200. (1992)

15.

Salmam, F. Z., Madani, A., & Kissi, M.: Facial expression recognition using decision trees. In Computer Graphics, Imaging and Visualization (CGiV), 2016 13th International Conference on (pp. 125–130). IEEE. (2016)

16.

Agada, R., & Yan, J.: A model of local binary pattern feature descriptor for valence facial expression classification. In Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on (pp. 634–639). IEEE (2015)

17.

Ou, J., Bai, X. B., Pei, Y., Ma, L., & Liu, W.: Automatic facial expression recognition using Gabor filter and expression analysis. In Computer Modeling and Simulation, 2010. ICCMS’10. Second International Conference on (Vol. 2, pp. 215–218). IEEE. (2010)

18.

Hussain, M., Khan, S. A., Ullah, N., Riaz, N., & Nazir, M.: Computationally Efficient Invariant Facial Expression Recognition. Research Journal of Recent Sciences, vol. 3, no. 2, pp. 61–68, (2014)

19.

Viola, P., & Jones, M.: Rapid object detection using a boosted cascade of simple features. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on (Vol. 1, pp. I-I). IEEE (2001)

20.

Kundu, S., & Ray, B.: An efficient chain code based face identification system for biometrics. In Signal Processing and Information Technology (ISSPIT), 2015 IEEE International Symposium on (pp. 559–564). IEEE (2015)

21.

Kundu, S., & Ray, B.: New hamming score based correlation method for fingerprint identification. In Computers and Devices for Communication (CODEC), International Conference on (pp. 1–4). IEEE (2015)

22.

Ma, L., Li, J., Ma, J., & Zhang, H.: A modified census transform based on the neighborhood information for stereo matching algorithm. In Image and Graphics (ICIG), 2013 Seventh International Conference on (pp. 533–538). IEEE (2013)

23.

Gehrig, T., & Ekenel, H. K.: A common framework for real-time emotion recognition and facial action unit detection. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on (pp. 1–6). IEEE (2011)

24.

Chang, C.-C., C.-J. Lin: LIBSVM: a library for support vector machines, http://www.csie.ntu.edu.tw/cjlin/libsvm, (2001)

25.

Kanade, T., Tian, Y., & Cohn, J. F.: Comprehensive database for facial expression analysis. In fg (p. 46). IEEE (2000)

26.

Lucey, P., Cohn, J. F., Kanade, T., Saragih, J., Ambadar, Z., & Matthews, I.: The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on (pp. 94–101). IEEE (2010)

27.

Lyons, M. J., Akamatsu, S., Kamachi, M., Gyoba, J., & Budynek, J.: The Japanese female facial expression (JAFFE) database. In Proceedings of third international conference on automatic face and gesture recognition, pp. 14–16 (1998)

28.

Chakraborty, A., Banerjee, J. S., & Chattopadhyay, A.: Malicious node restricted quantized data fusion scheme for trustworthy spectrum sensing in cognitive radio networks. Journal of mechanics of continua and mathematical sciences, 15(1), 39–56, (2020)

29.

Roy, R., Dutta, S., Biswas, S., Banerjee, J.S.: Android Things: A comprehensive solution from things to smart display and speaker. InProc. ICIIL 2019, 339–352 Springer, (2020)

Title: Facial Expression Recognition for Human Computer Interaction
Authors: Joyati Chattopadhyay
Souvik Kundu
Arpita Chakraborty
Jyoti Sekhar Banerjee
Publisher: Springer International Publishing
Book: New Trends in Computational Vision and Bio-inspired Computing
Print ISBN: 978-3-030-41861-8

Electronic ISBN: 978-3-030-41862-5

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-41862-5_119

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