Facial Emotion Recognition Using Transfer Learning of AlexNet

Sarmela A.P. Raja Sekaran, Chin Poo Lee, Kian Ming Lim

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

28 Citations (Scopus)

Abstract

In recent years, facial emotion recognition (FER) has become a prevalent research topic as it can be applied in various areas. The existing FER approaches include handcrafted feature-based methods (HCF) and deep learning methods (DL). HCF methods rely on how good the manual feature extractor can perform. The manually extracted features may be exposed to bias as it depends on the researcher's prior knowledge of the domain. In contrast, DL methods, especially Convolutional Neural Network (CNN), are good at performing image classification. The downfall of DL methods is that they require extensive data to train and perform recognition efficiently. Hence, we propose a deep learning method based on transfer learning of pre-trained AlexNet architecture for FER. We perform full model finetuning on the Alexnet, which was previously trained on the Imagenet dataset, using emotion datasets. The proposed model is trained and tested on two widely used facial expression datasets, namely extended Cohn-Kanade (CK+) dataset and FER dataset. The proposed framework outperforms the existing state-of-the-art methods in facial emotion recognition by achieving the accuracy of 99.44% and 70.52% for the CK+ dataset and the FER dataset.

Original languageEnglish
Title of host publication2021 9th International Conference on Information and Communication Technology, ICoICT 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages170-174
Number of pages5
ISBN (Electronic)9781665404471
DOIs
Publication statusPublished - 3 Aug 2021
Externally publishedYes
Event9th International Conference on Information and Communication Technology, ICoICT 2021 - Virtual, Yogyakarta, Indonesia
Duration: 3 Aug 20215 Aug 2021

Publication series

Name2021 9th International Conference on Information and Communication Technology, ICoICT 2021

Conference

Conference9th International Conference on Information and Communication Technology, ICoICT 2021
Country/TerritoryIndonesia
CityVirtual, Yogyakarta
Period3/08/215/08/21

Keywords

  • extended Cohn Kanade
  • facial emotion recognition
  • facial expression
  • FER2013
  • transfer learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems

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