Local directional gradients extension for recognising face and facial expressions
by Farid Ayeche; Adel Alti
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 20, No. 6, 2022

Abstract: This paper proposes new descriptors for recognising face and facial expressions. Our descriptors consist in combining local directional gradients with support vector machine (SVM) linear classification. This combination allows extracting discriminant facial expressions features for better classification accuracy with good efficiency than existing classifiers. Both descriptors are built based on the reduced texture features extracted from the face image based on magnitude and orientation maps on the horizontal and vertical coordinates. JAFFE and YALE benchmarks have been used to evaluate the accuracy and execution time of the requested face in the classification process. The experimental results are very promising and show that the proposed descriptors are effective and efficient compared to current works.

Online publication date: Wed, 25-Jan-2023

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