A Texture Features-Based Robust Facial Expression Recognition

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Author(s): Jayati Krishna Goswami (GLA University, India), Sunita Jalal (G. B. Pant University of Agriculture and Technology, India), Chetan Singh Negi (G. B. Pant University of Agriculture and Technology, India)and Anand Singh Jalal (GLA University, India)
Copyright: 2022
Volume: 12
Issue: 1
Pages: 15
Source title: International Journal of Computer Vision and Image Processing (IJCVIP)
DOI: 10.4018/IJCVIP.2022010103

Keywords: Artificial Intelligence / Computer Science & IT / Computer Vision & Image Processing / Information Science Reference

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Abstract

Facial expression plays an important role in communicating emotions. In this paper, a robust method for recognizing facial expressions is proposed using the combination of appearance features. Traditionally, appearance features mainly divide any face image into regular matrices for the computation of facial expression recognition. However, in this paper, we have computed appearance features in specific regions by extracting facial components such as eyes, nose, mouth, and forehead, etc. The proposed approach mainly has five stages to detect facial expression viz. face detection and regions of interest extraction, feature extraction, pattern analysis using a local descriptor, the fusion of appearance features and finally classification using a Multiclass Support Vector Machine (MSVM). Results of the proposed method are compared with the earlier holistic representations for recognizing facial expressions, and it is found that the proposed method outperforms state-of-the-art methods.

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A Texture Features-Based Robust Facial Expression Recognition

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