Henry Ugochukwu Ukwu*, Kamil Yurtkan
Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1819-1838, 2022, DOI:10.32604/iasc.2022.025695
Abstract The primary goal of this paper is to describe a proposed framework for identifying human face expressions. A methodology has been proposed and developed to identify facial emotions using an axes-angular feature extracted from facial landmarks for 4D dynamic facial expression video data. The 4D facial expression recognition (FER) problem is modeled as an unbalanced problem using the full video sequence. The proposed dataset includes landmarks that are positioned to be fiducial features: around the brows, eyes, nose, cheeks, and lips. Following the initial facial landmark preprocessing, feature extraction is carried out. Input feature vectors from gamma axes and magnitudes… More >
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