Analysis of HOG suitability for facial traits description in FER problems

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 on-line testing session has been added in order to prove the robustness of our approach in real environments.