Name
Abstract | ||
|---|---|---|
This paper introduces a skeleton calibration method for orientation measurement sensors based motion capture systems. In this method, the orientation sensors are used to measure the posture of the limbs. A template is used to register the end-effectors' postures (feet, hands for example). Through capturing the limb postures while the end-effectors match with the pre-defined postures on the template, a linear equation system of the skeleton dimensions can be generated based on the human kinematics. The limb dimension parameters can be optimized based on that. The identifiablility of this skeleton dimension is discussed. The symmetric property of the skeleton is also taken into consideration. To demonstrate the method, IMU sensors and a footprint template are used to calibrate the lower limb dimension. Results show the absolute dimension errors can be controlled within centimeter level for this human lower limb calibration. Compared with existing methods, this template based method is a quick and self-contained method which does not need extra measurement devices, and the skeleton model does not have asymmetric problems. Since the inertial MoCap systems are widely used nowadays, this method is useful to generate an accurate skeleton model for precise behavior presentation. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICRA.2013.6631335 | ICRA |
Keywords | Field | DocType |
medical robotics,biomechanics,linear equation system,inertial systems,calibration,robot kinematics,end effector posture registration,footprint template,inertial mocap systems,imu sensors,biomedical measurement,skeleton dimension generation,lower limb dimension calibration,motion capture systems,absolute dimension error control,end effectors,human lower limb calibration,self-contained method,limb posture measurement,skeleton dimension identifiablility,sensors,position measurement,symmetric property,limb dimension parameter optimization,template based method,human kinematics,orientation measurement sensors,skeleton model calibration method,kinematics,mathematical model | Inertial frame of reference,Computer vision,Motion capture,Kinematics,Robot kinematics,Control engineering,Robot end effector,Footprint,Inertial measurement unit,Artificial intelligence,Engineering,Calibration | Conference |
Volume | Issue | ISSN |
2013 | 1 | 1050-4729 |
ISBN | Citations | PageRank |
978-1-4673-5641-1 | 2 | 0.45 |
References | Authors | |
11 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qilong Yuan | 1 | 45 | 7.96 |
| I-Ming Chen | 2 | 567 | 87.28 |
| Ang Wei Sin | 3 | 2 | 0.45 |