Pose Estimation for Facilitating Movement Learning from Online Videos

04/07/2020
by   Atima Tharatipyakul, et al.
0

There exists a multitude of online video tutorials to teach physical movements such as exercises. Yet, users lack support to verify the accuracy of their movements when following such videos and have to rely on their own perception. To address this, we developed a web-based application that performs human pose estimation using both video inputs from the online video and web camera, then provides different types of visual feedback to a user. Our study suggests that the user's skeleton overlaid on the user's camera feed improved user performance, whereas the user's skeleton on its own or trainer's skeleton with the trainer video offered limited benefits. We believe that our application demonstrates the potential to enhance learning physical movements from online videos and provides a basis for other guidance systems to design suitable visualizations.

READ FULL TEXT

page 1

page 2

research
03/11/2023

GeoCamera: Telling Stories in Geographic Visualizations with Camera Movements

In geographic data videos, camera movements are frequently used and comb...
research
07/29/2021

SyncUp: Vision-based Practice Support for Synchronized Dancing

The beauty of synchronized dancing lies in the synchronization of body m...
research
04/19/2022

VCoach: A Customizable Visualization and Analysis System for Video-based Running Coaching

Videos are accessible media for analyzing sports postures and providing ...
research
04/04/2023

SportsPose – A Dynamic 3D sports pose dataset

Accurate 3D human pose estimation is essential for sports analytics, coa...
research
10/25/2020

Human or Machine? It Is Not What You Write, But How You Write It

Online fraud often involves identity theft. Since most security measures...
research
09/03/2021

Deep Learning for Fitness

We present Fitness tutor, an application for maintaining correct posture...

Please sign up or login with your details

Forgot password? Click here to reset