Human Pose Estimation for Training Assistance: a Systematic Literature Review

  • Gisela Miranda Difini UNISINOS
  • Márcio Garcia Martins UNISINOS
  • Jorge Luís Victória Barbosa UNISINOS


Human pose estimation is an important field of Computer Vision that aims to predict poses of individuals from videos and images. It has been used in many different areas including human-computer interaction, motion analysis, surveillance, action prediction, action correction, augmented reality, virtual reality, and healthcare. This review is focused on the most significant contributions in human pose estimation for training assistance. Executing movements correctly is crucial in all kinds of physical activities, both to increase performance and reduce risk of injury. Human pose estimation is poised to help athletes better analyse the quality of their movements. The systematic review study was conducted in five databases including articles from January 2011 to March 2021. The initial search resulted in 129 articles, of which 8 were selected after applying the filtering criteria. Moreover this study presents the challenges related to pose estimation, which pose estimation methods have been used in recent years, in which specific activities the selected articles have focused on, and a taxonomy of human pose estimation methods.
Palavras-chave: human pose estimation, pose tracking, training assistance, sports, systematic review
Como Citar

Selecione um Formato
DIFINI, Gisela Miranda; MARTINS, Márcio Garcia; BARBOSA, Jorge Luís Victória. Human Pose Estimation for Training Assistance: a Systematic Literature Review. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 1. , 2021, Minas Gerais. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 189-196.