Computational Science and Its Applications ICCSA 2019
The study proposes and tests a technique for automated emotion recognition
through mouth detection via Convolutional Neural Networks (CNN), meant to be
applied for supporting people with health disorders with communication skills
issues (e.g. muscle wasting, stroke, autism, or, more simply, pain) in order to
recognize emotions and generate real-time feedback, or data feeding supporting
systems. The software system starts the computation identifying if a face is
present on the acquired image, then it looks for the mouth location and
extracts the corresponding features. Both tasks are carried out using Haar
Feature-based Classifiers, which guarantee fast execution and promising
performance. If our previous works focused on visual micro-expressions for
personalized training on a single user, this strategy aims to train the system
also on generalized faces data sets.
Giulio Biondi, Valentina Franzoni, Osvaldo Gervasi, Damiano Perri
2022-12-12
