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A Texture Features-Based Robust Facial Expression Recognition

A Texture Features-Based Robust Facial Expression Recognition

Jayati Krishna Goswami, Sunita Jalal, Chetan Singh Negi, Anand Singh Jalal
Copyright: © 2022 |Volume: 12 |Issue: 1 |Pages: 15
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781683182122|DOI: 10.4018/IJCVIP.2022010103
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MLA

Goswami, Jayati Krishna, et al. "A Texture Features-Based Robust Facial Expression Recognition." IJCVIP vol.12, no.1 2022: pp.1-15. http://doi.org/10.4018/IJCVIP.2022010103

APA

Goswami, J. K., Jalal, S., Negi, C. S., & Jalal, A. S. (2022). A Texture Features-Based Robust Facial Expression Recognition. International Journal of Computer Vision and Image Processing (IJCVIP), 12(1), 1-15. http://doi.org/10.4018/IJCVIP.2022010103

Chicago

Goswami, Jayati Krishna, et al. "A Texture Features-Based Robust Facial Expression Recognition," International Journal of Computer Vision and Image Processing (IJCVIP) 12, no.1: 1-15. http://doi.org/10.4018/IJCVIP.2022010103

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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.