Paper Info
Title
Human Pose Estimation for Training Assistance: a Systematic Literature Review
Abstract
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.
Year
DOI
Venue
2021
10.1145/3470482.3479633
PROCEEDINGS OF THE 27TH BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA '21)
Keywords
DocType
Citations 
human pose estimation, pose tracking, training assistance, sports, systematic review
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Gisela Miranda Difini100.34
Márcio Garcia Martins200.34
Jorge Luis Victória Barbosa37329.37