Titre :

Where Is My Mind (Looking at)? A Study of the EEG–Visual Attention Relationship

Auteur(s) :

Delvigne, Victor [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Faculté polytechnique de Mons
Tits, Noé [Auteur]
Faculté polytechnique de Mons
La Fisca, Luca [Auteur]
Faculté polytechnique de Mons
Hubens, Nathan [Auteur]
Institut Polytechnique de Paris [IP Paris]
Faculté polytechnique de Mons
Maiorca, Antoine [Auteur]
Faculté polytechnique de Mons
Wannous, Hazem [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]
Dutoit, Thierry [Auteur]
Faculté polytechnique de Mons
Vandeborre, Jean Philippe [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Nord Europe]

Titre de la revue :

Informatics

Pagination :

26

Éditeur :

MDPI

Date de publication :

2022-03

ISSN :

2227-9709

Discipline(s) HAL :

Sciences du Vivant [q-bio]/Neurosciences [q-bio.NC]/Sciences cognitives
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Apprentissage [cs.LG]
Informatique [cs]/Traitement du signal et de l'image [eess.SP]

Résumé en anglais : [en]

Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, deep learning, and medicine. One of the most common approaches to estimate a saliency map representing ...
Lire la suite >Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, deep learning, and medicine. One of the most common approaches to estimate a saliency map representing attention is based on the observed images. In this paper, we show that visual attention can be retrieved from EEG acquisition. The results are comparable to traditional predictions from observed images, which is of great interest. Image-based saliency estimation being participant independent, the estimation from EEG could take into account the subject specificity. For this purpose, a set of signals has been recorded, and different models have been developed to study the relationship between visual attention and brain activity. The results are encouraging and comparable with other approaches estimating attention with other modalities. Being able to predict a visual saliency map from EEG could help in research studying the relationship between brain activity and visual attention. It could also help in various applications: vigilance assessment during driving, neuromarketing, and also in the help for the diagnosis and treatment of visual attention-related diseases. For the sake of reproducibility, the codes and dataset considered in this paper have been made publicly available to promote research in the field.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL