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.