4卷 第1期
Sichuan University
纸质出版日期： 2023 ，
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(2023). A Novel Multi-Person Pose Estimation Using in Indoor Fitness. 科技理论与实践（英文版）, 4(1), 97-111.
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..
(2023). A Novel Multi-Person Pose Estimation Using in Indoor Fitness. 科技理论与实践（英文版）, 4(1), 97-111. DOI： 10.47297/taposatWSP2633-456916.20230401.
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.
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
Computer visionHuman pose estimationYOLOv5MediaPipe
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