Facial Expression Classification Using Artificial Neural Network and K-Nearest Neighbor

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Tran Son Hai 1,* Le Hoang Thai 2 Nguyen Thanh Thuy 3

1. Informatics Technology Department, University of Pedagogy, Ho Chi Minh City, Vietnam, member of IACSIT

2. Computer Science Department, University of Science, Ho Chi Minh City, Vietnam

3. University of Technology, Ha Noi City, Vietnam

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2015.03.04

Received: 19 Jun. 2014 / Revised: 2 Oct. 2014 / Accepted: 27 Nov. 2014 / Published: 8 Feb. 2015

Index Terms

Facial Expression Classification, Artificial Neural Network (ANN), K-Nearest Neighbor (K-NN), Independent Component Analysis (ICA)


Facial Expression is a key component in evaluating a person's feelings, intentions and characteristics. Facial Expression is an important part of human-computer interaction and has the potential to play an equal important role in human-computer interaction. The aim of this paper is bring together two areas in which are Artificial Neural Network (ANN) and K-Nearest Neighbor (K-NN) applying for facial expression classification. We propose the ANN_KNN model using ANN and K-NN classifier. ICA is used to extract facial features. The ratios feature is the input of K-NN classifier. We apply ANN_KNN model for seven basic facial expression classifications (anger, fear, surprise, sad, happy, disgust and neutral) on JAFEE database. The classifying precision 92.38% has been showed the feasibility of our proposal model.

Cite This Paper

Tran Son Hai, Le Hoang Thai, Nguyen Thanh Thuy, "Facial Expression Classification Using Artificial Neural Network and K-Nearest Neighbor", International Journal of Information Technology and Computer Science(IJITCS), vol.7, no.3, pp.27-32, 2015. DOI:10.5815/ijitcs.2015.03.04


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