Automatic Facial Expressions and Identification of different face reactions using Convolutional Neural Network
Anand R1, Kalkeseetharaman P. K.2, Naveen Kumar S3
1Anand R, Assistant Professor, Department of ECE, Salem.
2Kalkeseetharaman P.K, Department of ECE, Sona College of Technology, Salem.
3Naveen Kumar S, Department of ECE, Sona College of Technology, Salem.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 5214-5217 | Volume-8 Issue-12, October 2019. | Retrieval Number: L27821081219/2019©BEIESP | DOI: 10.35940/ijitee.L2782.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Automatic Face expression is the significant device in computer apparition and a predictable knowledge discovery application in automation, personal security and moveable devices. However, the state-of-the-art machine and deep learning (DL) methods has complete this technology game altering and even better human matching part in terms of accurateness. This paper focuses on put on one of the progressive deep learning tools in face expression to achieve higher accuracy. In this paper, we focusses on Automatic Facial Expressions and Identification of different face reactions using Convolution Neural Network. Here, we framed our own data and trained by convolution neural networks. Human behavior can be easily predicted using their facial expression, which helps marketing team, psychological team and other required team to understand the human facial expression more clearly.
Keywords: Convolutional Neural Network, Pooling layer, Deep learning, Artificial Intelligence, Face expression.
Scope of the Article: Artificial Intelligence