Title :

Pain Detection From Facial Expressions Based on Transformers and Distillation

Author(s) :

El Morabit, Safaa [Auteur]
Université Polytechnique Hauts-de-France [UPHF]
Rivenq, Atika [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
COMmunications NUMériques - IEMN [COMNUM - IEMN]

Conference title :

2022 11th International Symposium on Signal, Image, Video and Communications (ISIVC)

City :

El Jadida

Country :

Maroc

Start date of the conference :

2022-05-18

Book title :

2022 11th International Symposium on Signal, Image, Video and Communications (ISIVC)

Publisher :

IEEE

English keyword(s) :

Heating systems
Deep learning
Emotion recognition
Image recognition
Pain
Databases
Biological system modeling

HAL domain(s) :

Sciences de l'ingénieur [physics]

English abstract : [en]

Pain assessment is a challenging problem in the field of emotion recognition. Pain represents a complex emotion difficult to detect or to estimate its intensity. This is what makes automatic pain assessment playing an ...
Show more >Pain assessment is a challenging problem in the field of emotion recognition. Pain represents a complex emotion difficult to detect or to estimate its intensity. This is what makes automatic pain assessment playing an important role in clinical diagnosis. Taking into consideration that pain generally generates spontaneous facial behaviour, these facial expressions could be used to detect the presence of pain. As a matter of fact, previous researches used machine learning and deep learning either to detect pain or to estimate pain level. In this paper, we propose a fine-tuning of pre-trained data-efficient image transformers and distillation (Deit) for pain detection from facial expressions. The effectiveness of the proposed architecture is evaluated on two publicly available databases, namely UNBC McMaster Shoulder Pain and BioVid Heat Pain. The proposed approach achieved promising preliminary results compared to the state of the art.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL