A mobile application to report and detect 3D body emotional poses

García-Magariño, I. ; Cerezo, E. (Universidad de Zaragoza) ; Plaza, I. (Universidad de Zaragoza) ; Chittaro, L.

Resumen: Most research into automatic emotion recognition is focused on facial expressions or physiological signals, while the exploitation of body postures has scarcely been explored, although they can be useful for emotion detection. This paper first explores a mechanism for self-reporting body postures with a novel easy-to-use mobile application called EmoPose. The app detects emotional states from self-reported poses, classifying them into the six basic emotions proposed by Ekman and a neutral state. The poses identified by Schindler et al. have been used as a reference and the nearest neighbor algorithm used for the classification of poses. Finally, the accuracy in detecting emotions has been assessed by means of poses reported by a sample of users.

Idioma: Inglés

DOI: 10.1016/j.eswa.2019.01.021

Año: 2019

Publicado en: Expert Systems with Applications 122 (2019), 207-216
ISSN: 0957-4174

Factor impacto JCR: 5.452 (2019)

Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 21 / 136 = 0.154 (2019) - Q1 - T1
Categ. JCR: OPERATIONS RESEARCH & MANAGEMENT SCIENCE rank: 2 / 83 = 0.024 (2019) - Q1 - T1
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 32 / 266 = 0.12 (2019) - Q1 - T1

Factor impacto SCIMAGO: 1.494 - Artificial Intelligence (Q1) - Engineering (miscellaneous) (Q1) - Computer Science Applications (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FEDER/Construyendo Europa desde Aragón
Financiación: info:eu-repo/grantAgreement/ES/DGA/T25-17D
Financiación: info:eu-repo/grantAgreement/ES/MEC/CAS16-00075
Financiación: info:eu-repo/grantAgreement/ES/MEC/CAS17-00005
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2015-67149-C3-1-R
Financiación: info:eu-repo/grantAgreement/ES/UZ/IT24-16
Financiación: info:eu-repo/grantAgreement/ES/UZ/IT6-15
Financiación: info:eu-repo/grantAgreement/ES/UZ/JIUZ-2017-TEC-03
Financiación: info:eu-repo/grantAgreement/ES/UZ/UZ2017-TEC-02

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Tecnología Electrónica (Dpto. Ingeniería Electrón.Com.)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)