A Novel Multi-Person Pose Estimation Using in Indoor Fitness

Mao; Z; Zhou

doi:10.47297/taposatWSP2633-456916.20230401

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A Novel Multi-Person Pose Estimation Using in Indoor Fitness

Volume 4, Issue 1

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A Novel Multi-Person Pose Estimation Using in Indoor Fitness
A Novel Multi-Person Pose Estimation Using in Indoor Fitness
Sichuan University
Vol. 4, Issue 1, Pages: 97-111(2023)
Published： 2023 ，
DOI：10.47297/taposatWSP2633-456916.20230401
Accepted：

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MAO, Z & ZHOU. (2023). A Novel Multi-Person Pose Estimation Using in Indoor Fitness. Theory and Practice of Science and Technology, 4(1), 97-111..
DOI：

MAO, Z & ZHOU. (2023). A Novel Multi-Person Pose Estimation Using in Indoor Fitness. Theory and Practice of Science and Technology, 4(1), 97-111.. DOI： 10.47297/taposatWSP2633-456916.20230401.

摘要

Abstract

In the post-pandemic era

online fitness has become a new trend. Compare to traditional fitness in gym

online fitness is convenient

but lack of action guidance

which cannot guarantee the quality and may lead to the injures. Therefore

to monitor the accuracy of online fitness is required. The existing fitness monitor often relies on special hardware

such as smart TV

depth camera or multi-sensors

which have high cost

inconvenient installation and limited scenarios. With the development of human joint points detection technology

the estimation of human pose can be achieved through a monocular RGB camera

which makes it possible to achieve low cost

high speed and multi-scenarios monitor on laptop or mobile phone. Based on above

this paper proposes a novel multi-person pose estimation method based on YOLOv5 & MediaPipe

using in indoor fitness. We also propose an algorithm to measure human joint points angle in 3D scenario

from a monocular RGB camera

and provide feedback via audio. The prototype is implemented and the performance is verified under 3 fitness poses. The results show that the proposed method and prototype has high accuracy and practical value. CCS CONCEPTS • Insert your first CCS term here • Insert your second CCS term here • Insert your third CCS term here

关键词

Keywords

Computer visionHuman pose estimationYOLOv5MediaPipe

references

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