Analysis of HOG suitability for facial traits description in FER problems

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Abstract

Automatic Facial Expression Recognition is a topic of high interest especially due to the growing diffusion of assistive computing applications, as Human Robot Interaction, where a robust awareness of the people emotion is a key point. This paper proposes a novel automatic pipeline for facial expression recognition based on the analysis of the gradients distribution, on a single image, in order to characterize the face deformation in different expressions. Firstly, an accurate investigation of optimal HOG parameters has been done. Successively, a wide experimental session has been performed demonstrating the higher detection rate with respect to other State-of-the-Art methods. Moreover, an online testing session has been added in order to prove the robustness of our approach in real environments.

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Del Coco, M., Carcagnì, P., Palestra, G., Leo, M., & Distante, C. (2015). Analysis of HOG suitability for facial traits description in FER problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9280, pp. 460–471). Springer Verlag. https://doi.org/10.1007/978-3-319-23234-8_43

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