Improving human emotion recognition from emotive videos using geometric data augmentation

Nusrat J. Shoumy, Li Minn Ang, D. M.Motiur Rahaman, Tanveer Zia, Kah Phooi Seng, Sabira Khatun

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

Emotional recognition from videos or images requires large amount of data to obtain high performance and classification accuracy. However, large datasets are not always easily available. A good solution to this problem is to augment the data and extrapolate it to create a bigger dataset for training the classifier. In this paper, we evaluate the impact of different geometric data augmentation (GDA) techniques on emotion recognition accuracy using facial image data. The GDA techniques that were implemented were horizontal reflection, cropping, rotation separately and combined. In addition to this, our system was further evaluated with four different classifiers (Convolutional Neural Network (CNN), Linear Discriminant Analysis (LDA), K-Nearest Neighbor (kNN) and Decision Tree (DT)) to determine which of the four classifiers achieves the best results. In the proposed system, we used augmented data from a dataset (SAVEE) to perform training, and testing was carried out by the original data. A combination of GDA techniques using the CNN classifier was found to give the best performance of approximately 97.8%. Our system with GDA augmentation was shown to outperform previous approaches where only the original dataset was used for classifier training.

Original languageEnglish
Title of host publicationAdvances and Trends in Artificial Intelligence. From Theory to Practice
Subtitle of host publication34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Proceedings, Part II
EditorsHamido Fujita, Ali Selamat, Jerry Chun-Wei Lin, Moonis Ali
PublisherSpringer
Pages149-161
Number of pages13
Volume12799
ISBN (Electronic)9783030794637
ISBN (Print)9783030794620
DOIs
Publication statusE-pub ahead of print - 19 Jul 2021
Event34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021 - Virtual conference
Duration: 26 Jul 202129 Jul 2021
https://ieaaie2021.wordpress.com/ (Conference website)
https://jsasaki3.wixsite.com/website-4 (Conference schedule)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12799 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021
Period26/07/2129/07/21
OtherThe 34th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems IEA/AIE 2021 continues the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation & robotics, business & finance, medicine and biomedicine, bioinformatics, cyberspace, and human-machine.
Internet address

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