Human Skeleton Detection, Modeling and Gesture Imitation Learning for a Social Purpose - Archive ouverte HAL Access content directly
Journal Articles Engineering Year : 2020

Human Skeleton Detection, Modeling and Gesture Imitation Learning for a Social Purpose

(1) , (2, 3) , (2, 3) , (2, 3) , (1)
1
2
3

Abstract

Gesture recognition is topical in computer science and aims at interpreting human gestures via mathematical algorithms. Among the numerous applications are physical rehabilitation and imitation games. In this work, we suggest performing human gesture recognition within the context of a serious imitation game, which would aim at improving social interactions with teenagers with autism spectrum disorders. We use an artificial intelligence algorithm to detect the skeleton of the participant, then model the human pose space and describe an imitation learning method using a Gaussian Mixture Model in the Riemannian manifold.
Fichier principal
Vignette du fichier
2020ValleeEngineering.pdf (1.73 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02894323 , version 1 (08-07-2020)

Identifiers

Cite

Linda Nanan Vallée, Sao Mai Nguyen, Christophe Lohr, Ioannis Kanellos, Olivier Asseu. Human Skeleton Detection, Modeling and Gesture Imitation Learning for a Social Purpose. Engineering, 2020, 12 (02), pp.90-98. ⟨10.4236/eng.2020.122009⟩. ⟨hal-02894323⟩
85 View
206 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More