automatic joint parameter estimation from magnetic motion capturedata james f.o”brien robert e....
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Automatic Joint Parameter Estimation from Magnetic Motion CaptureData
James F.O”Brien Robert E. Bodenheimer Gabriel J Brostow Jessica K. Hodgins
Presented by Ws Hong.
Goal
Limb linghts, joint locationsAnd sensor placement
Mocap data for Human subject
determine
A hierarchical stucture
inferred
Perform FK and IK procedures
1. An automatic method for computing limb lengths, joint locations and sensor placementFrom magnetic motion capture data
2. The result of using the algorithm on mocap data and validation result from simulation
The related work
Inside of graphics1. Silaghi and colleagure[18] Iidentifying an anatomic skeleton from opticla motion capture Data
2. Bodenheimer and colleagure[2] Inverse kinematics are often used to extract joint angles from gobal position data
Outside of graphics1. Biomechanics[15,16] The problem of determining a system’s kinematic parameters from the motion of the system
2. Robotics[15,16] Interested in similar questions because they need to calibrate physical devices
Methods<Example of an articulated hierarchy>
Arrows : outboard direction
jiLet
Transformation …forIth body coordinate to jth Body coordinate
ji Translational component
Rotational component
jit
jiR
Transformation : I-th coordinate system to j-th coordinate system
jiijij txRx
It may be inverted
)()(
)(1
1
jijiij
jiij
tRt
RR
iiiPi
kiiPi
k
iiiiPi
kiP
lcRxR
lcxRx
)()(
)()( )(
In terms of Ci and li….
Finding Joint Location
iiiPi
kiPi lcRt )()(
iiiPi
kiiPi
kiPi
kiiPi
k lcRxRtxR )()()()(
By applying to both sides ji
To matrix form
<6 length vector>
3n by 6 matrix 3n by 1 matrix
After determination of the locations for the joints…..The Body Hierarchy :Each body a nodeJoints edge between bodyJoint fit error Weight of edge
Minimal spanning tree Determinatethe Hierarchy
ResultTest on something less complicated than bio-logical joints
Wooden mechanical linkage with 5 ball
Motion capture sensors
The model computed from Mocap data
A comparison of measurements and calculated limb length for six data sets of theMechanical linkage
The maximum error is 1.1The hierarchy was computed correctly
The residual vectors from the least squares process
All data is less than 1.0
The error is on the order of the resolution of the sensors
Comparing residual errors between the mechanical linkage and a male subject
Residual errors of the right shoulder for the mechanical linkage
Residual errors of the data from Walk2 of a male subject
Error is Much larger than for the mechanical linkage
A comparison of measurements and calculated limb lengths for four data sets of a male subject
Maximum difference 4.1 at left upper armFind big error in left upper arm continuesly due to an error measured by hand?
Maximum difference –2.4 is also at left upper arm It is less than that for male testMean difference for more than 1centimeters right lower leg, left upper leg, left upper arm
Conclusion
1. An automatic method for computing limb lengths, joint locations and sensor placement from magnetic motion capture data.
2. Produced results accurate to the resulution of the sensors for data.
3. The algorithm would also be of use in applications for the problem fitting data to a graphical model
4. The algorithm for marker identification can be used to extract the hierarchy automatically.