Facial Expression Recognition using Local Gabor Binary Pattern(LGBP) and Principle Component Analysis (PCA)

SHALU, GUPTA and SONIT, SINGH (2014) Facial Expression Recognition using Local Gabor Binary Pattern(LGBP) and Principle Component Analysis (PCA). In: International Conference on Advances In Engineering And Technology - ICAET 2014, 24 - 25 May, 2014, RIT, Roorkee, India.

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Abstract

Facial Expression Recognition is one of the active research area in the field of Human Machine Interaction (HMI) because of its several applications such as human emotion analysis, stress level and lie detection. In this paper, an algorithm for facial expression recognition has been proposed which integrate the Local Binary Patterns (LBP), Gabor filter and Principal Component Analysis (PCA). The proposed technique has been applied on JAFFE database. The comparative analysis on the basis of average recognition rate has been performed for each individual and integrated approach. The results shows highest recognition rate while combining LGBP and PCA, which is 87.5. The results indicate that when we integrate LBP, Gabor filter and PCA, then it provides high recognition rate.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Facial expression analysis (FER), Principal Component Analysis (PCA), Local Gabor Binary Patterns (LGBP), Gabor filter. (key words)
Depositing User: Mr. John Steve
Date Deposited: 21 May 2019 11:44
Last Modified: 21 May 2019 11:44
URI: http://publications.theired.org/id/eprint/2615

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