Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model

2008 ◽  
pp. 248-258 ◽  
Author(s):  
Jan Bandouch ◽  
Florian Engstler ◽  
Michael Beetz
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Human Model ◽  
Human Motion Capture

scholarly journals Real-Time Human Motion Capture Driven by a Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Peng-zhan Chen ◽  
Jie Li ◽  
Man Luo ◽  
Nian-hua Zhu
Keyword(s):  
Real Time ◽  
Sensor Network ◽  
Motion Capture ◽  
Human Motion ◽  
Human Model ◽  
Human Skeleton ◽  
Inertial Sensing ◽  
Skeleton Model ◽  
Human Motion Capture ◽  
Motion Capture Systems

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.

scholarly journals Markerless Human Motion Capture from Voxel Reconstruction with Simple Human Model

2008 ◽  
Vol 2 (6) ◽  
pp. 985-997 ◽  
Author(s):  
Kazuhiko TAKAHASHI ◽  
Yusuke NAGASAWA ◽  
Masafumi HASHIMOTO
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Human Model ◽  
Human Motion Capture

Keyframe Extraction for Human Motion Capture Data Based on Joint Kernel Sparse Representation

2017 ◽  
Vol 64 (2) ◽  
pp. 1589-1599 ◽  
Author(s):  
Guiyu Xia ◽  
Huaijiang Sun ◽  
Xiaoqing Niu ◽  
Guoqing Zhang ◽  
Lei Feng
Keyword(s):  
Sparse Representation ◽  
Motion Capture ◽  
Human Motion ◽  
Motion Capture Data ◽  
Human Motion Capture ◽  
Keyframe Extraction

scholarly journals Dealing with Magnetic Disturbances in Human Motion Capture: A Survey of Techniques

Micromachines ◽  
2016 ◽  
Vol 7 (3) ◽  
pp. 43 ◽  
Author(s):  
Gabriele Ligorio ◽  
Angelo Sabatini
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
Human Motion Capture ◽  
Magnetic Disturbances

Sensor network oriented human motion capture via wearable intelligent system

2021 ◽  
Author(s):  
Sen Qiu ◽  
Hongkai Zhao ◽  
Nan Jiang ◽  
Donghui Wu ◽  
Guangcai Song ◽  
...  
Keyword(s):  
Sensor Network ◽  
Motion Capture ◽  
Intelligent System ◽  
Human Motion ◽  
Human Motion Capture

Human Motion Capture Driven by Orientation Measurements

1999 ◽  
Vol 8 (2) ◽  
pp. 187-203 ◽  
Author(s):  
Tom Molet ◽  
Ronan Boulic ◽  
Daniel Thalmann
Keyword(s):  
Motion Capture ◽  
Human Motion ◽  
High Rate ◽  
Position Measurement ◽  
Human Motion Capture ◽  
Fast Tracking ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Tracking Object ◽  
Capture Techniques

Motion-capture techniques are rarely based on orientation measurements for two main reasons: (1) optical motion-capture systems are designed for tracking object position rather than their orientation (which can be deduced from several trackers), (2) known animation techniques, like inverse kinematics or geometric algorithms, require position targets constantly, but orientation inputs only occasionally. We propose a complete human motion-capture technique based essentially on orientation measurements. The position measurement is used only for recovering the global position of the performer. This method allows fast tracking of human gestures for interactive applications as well as high rate recording. Several motion-capture optimizations, including the multijoint technique, improve the posture realism. This work is well suited for magnetic-based systems that rely more on orientation registration (in our environment) than position measurements that necessitate difficult system calibration.

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