Real-Time Human Motion Capture Driven by a Wireless Sensor Network
The motion of a real object model is reconstructed through measurements of the position, direction, and angle of moving objects in 3D space in a process called “motion capture.” With the development of inertial sensing technology, motion capture systems that are based on inertial sensing have become...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2015/695874 |
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| _version_ | 1832545617286529024 |
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| author | Peng-zhan Chen Jie Li Man Luo Nian-hua Zhu |
| author_facet | Peng-zhan Chen Jie Li Man Luo Nian-hua Zhu |
| author_sort | Peng-zhan Chen |
| collection | DOAJ |
| description | The motion of a real object model is reconstructed through measurements of the position, direction, and angle of moving objects in 3D space in a process called “motion capture.” With the development of inertial sensing technology, motion capture systems that are based on inertial sensing have become a research hot spot. However, the solution of motion attitude remains a challenge that restricts the rapid development of motion capture systems. In this study, a human motion capture system based on inertial sensors is developed, and the real-time movement of a human model controlled by real people’s movement is achieved. According to the features of the system of human motion capture and reappearance, a hierarchical modeling approach based on a 3D human body model is proposed. The method collects articular movement data on the basis of rigid body dynamics through a miniature sensor network, controls the human skeleton model, and reproduces human posture according to the features of human articular movement. Finally, the feasibility of the system is validated by testing of system properties via capture of continuous dynamic movement. Experiment results show that the scheme utilizes a real-time sensor network-driven human skeleton model to achieve the accurate reproduction of human motion state. The system also has good application value. |
| format | Article |
| id | doaj-art-fb010cc69b0b4c7ebadba9886342a895 |
| institution | Kabale University |
| issn | 1687-7047 1687-7055 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Computer Games Technology |
| spelling | doaj-art-fb010cc69b0b4c7ebadba9886342a8952025-02-03T07:25:19ZengWileyInternational Journal of Computer Games Technology1687-70471687-70552015-01-01201510.1155/2015/695874695874Real-Time Human Motion Capture Driven by a Wireless Sensor NetworkPeng-zhan Chen0Jie Li1Man Luo2Nian-hua Zhu3College of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang, Jiangxi 330013, ChinaCollege of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang, Jiangxi 330013, ChinaCollege of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang, Jiangxi 330013, ChinaCollege of Electrical and Electronic Engineering, East China Jiaotong University, Nanchang, Jiangxi 330013, ChinaThe motion of a real object model is reconstructed through measurements of the position, direction, and angle of moving objects in 3D space in a process called “motion capture.” With the development of inertial sensing technology, motion capture systems that are based on inertial sensing have become a research hot spot. However, the solution of motion attitude remains a challenge that restricts the rapid development of motion capture systems. In this study, a human motion capture system based on inertial sensors is developed, and the real-time movement of a human model controlled by real people’s movement is achieved. According to the features of the system of human motion capture and reappearance, a hierarchical modeling approach based on a 3D human body model is proposed. The method collects articular movement data on the basis of rigid body dynamics through a miniature sensor network, controls the human skeleton model, and reproduces human posture according to the features of human articular movement. Finally, the feasibility of the system is validated by testing of system properties via capture of continuous dynamic movement. Experiment results show that the scheme utilizes a real-time sensor network-driven human skeleton model to achieve the accurate reproduction of human motion state. The system also has good application value.http://dx.doi.org/10.1155/2015/695874 |
| spellingShingle | Peng-zhan Chen Jie Li Man Luo Nian-hua Zhu Real-Time Human Motion Capture Driven by a Wireless Sensor Network International Journal of Computer Games Technology |
| title | Real-Time Human Motion Capture Driven by a Wireless Sensor Network |
| title_full | Real-Time Human Motion Capture Driven by a Wireless Sensor Network |
| title_fullStr | Real-Time Human Motion Capture Driven by a Wireless Sensor Network |
| title_full_unstemmed | Real-Time Human Motion Capture Driven by a Wireless Sensor Network |
| title_short | Real-Time Human Motion Capture Driven by a Wireless Sensor Network |
| title_sort | real time human motion capture driven by a wireless sensor network |
| url | http://dx.doi.org/10.1155/2015/695874 |
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