Automatic Facial Expression Recognition Using DCNN

Research output: Contribution to journalArticlepeer-review

88 Citations (Scopus)


Face depicts a wide range of information about identity, age, sex, race as well as emotional and mental state. Facial expressions play crucial role in social interactions and commonly used in the behavioral interpretation of emotions. Automatic facial expression recognition is one of the interesting and challenging problem in computer vision due to its potential applications such as Human Computer Interaction(HCI), behavioral science, video games etc. In this paper, a novel method for automatically recognizing facial expressions using Deep Convolutional Neural Network(DCNN) features is proposed. The proposed model focuses on recognizing the facial expressions of an individual from a single image. The feature extraction time is significantly reduced due to the usage of general purpose graphic processing unit (GPGPU). From an evaluation on two publicly available facial expression datasets, we have found that using DCNN features, we can achieve the state-of-the-art recognition rate.

Original languageEnglish
Pages (from-to)453-461
Number of pages9
JournalProcedia Computer Science
Publication statusPublished - 2016

All Science Journal Classification (ASJC) codes

  • General Computer Science


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