Anna Di Lorenzo
Use of a multimodal Neural Network to investigate cultural and gender biases in affective stimuli of a novel facial expression database.
Rel. Federica Marcolin, Luca Ulrich, Alberto Raposo, Daniel Mograbi. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Abstract
Artificial Intelligence is about the replication of human intelligence in machines that are programmed to think as humans and imitate their actions. A human characteristic is the one of decoding the facial expression related to a determined emotion of other humans and this is necessary for the coexistence. In order to reproduce this peculiarity, the studies aimed to create empathetic machines able to recognize the facial expression of the facing human. This technique called Facial Expression Recognition (FER), is fundamental to a robot to understand the feelings in order to react consequently considering the perceived emotion. The interest towards this technique is increasing rapidly, so the purpose of the 3D Lab of Polytechnic of Turin was to create a database made up human spontaneous emotions collected with an experiment in collaboration with the Pontif´ıcia Universidade Cat´olica do Rio de Janeiro.
The experiment was conducted in Brazil, among brazilian partecipants, showing them a dataset of 48 images carefully chosen between two of the most world??wide known affective database, International Affective Picture System (IAPS) and Geneva Affective PicturE Database (GAPED)
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