Quantum-inspired binary gravitational search algorithm to recognize the facial expressions

Yogesh Kumar, Shashi Kant Verma () and Sandeep Sharma ()
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Yogesh Kumar: Department of Computer Science and Engineering, Uttarakhand Technical University, Dehradun Uttarakhand 248007, India
Shashi Kant Verma: Department of Computer Science and Engineering, Govind Ballabh Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand 246194, India
Sandeep Sharma: Centre for Reliability Sciences and Technologies, Department of Electronic Engineering, Chang Gung University, Taoyuan 33302, Taiwan

International Journal of Modern Physics C (IJMPC), 2020, vol. 31, issue 10, 1-24

Abstract: This paper addresses an autonomous facial expression recognition system using the feature selection approach of the Quantum-Inspired Binary Gravitational Search Algorithm (QIBGSA). The detection of facial features completely depends upon the selection of precise features. The concept of QIBGSA is a modified binary version of the gravitational search algorithm by mimicking the properties of quantum mechanics. The QIBGSA approach reduces the computation cost for the initial extracted feature set using the hybrid approach of Local binary patterns with Gabor filter method. The proposed automated system is a sequential system with experimentation on the image-based dataset of Karolinska Directed Emotional Faces (KDEF) containing human faces with seven different emotions and different yaw angles. The experiments are performed to find out the optimal emotions using the feature selection approach of QIBGSA and classification using a deep convolutional neural network for robust and efficient facial expression recognition. Also, the effect of variations in the yaw angle (front to half side view) on facial expression recognition is studied. The results of the proposed system for the KDEF dataset are determined in three different cases of frontal view, half side view, and combined frontal and half side view images. The system efficacy is analyzed in terms of recognition rate.

Keywords: Gravitational search algorithm; quantum mechanics; quantum computing; binary gravitational search algorithm; deep convolutional neural network; facial expression recognition; pose variation; yaw angle (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0129183120501387

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