RT Journal Article
T1 A mobile application to report and detect 3D body emotional poses
A1 García-Magariño, Iván
A1 Cerezo, Eva
A1 Plaza, Inmaculada
A1 Chittaro, Luca
AB 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.
PB Elsevier
YR 2019
FD 2019-05-15
LK https://hdl.handle.net/20.500.14352/112752
UL https://hdl.handle.net/20.500.14352/112752
LA eng
NO García-Magariño, I., Cerezo, E., Plaza, I., & Chittaro, L. (2019). A mobile application to report and detect 3D body emotional poses. Expert Systems with Applications, 122, 207-216
NO Foundation Ibercaja
DS Docta Complutense
RD 25 abr 2025