1

Motion capture

• Principle

• Harware

• Data fitting

Principle

• Capture movements or postures in the realworld– actor (body, hands, face)

– puppet (body)

• Extract relevant data

• Use data– Map the movements to a synthetic creature

– Execute commands

2

Capture harware

• Magnetic sensors

• Optical capture

• Rotation encoders (puppet)

Magnetic sensors

3

Data flow

• Source and sensors– emit and receive magnetic fields

• Electronic control unit– computes positions and orientations (6D)

• Server/driver– sends the data to the computer(s)

– one channel/sensor

• Tracks(one/variable)

Practice

• Wired actor– 10-20 sensors

• Data sampling– 15-120 Hz

4

Advantages of magnetic motioncapture

• Position and orientation

• Minimal device calibration

• Real-time

• Cheap ($40000)

Disadvantages of magneticmotion capture

• Limited range– 10-15 m2

• Sensitivity to metal

• Encumbrance

• Sampling rate

5

Optical capture

• Use retro-reflective markers– circular stickers

– small spheres

• Cameras– facial animation: 1

– body animation: 2-6

• Postprocessing of images

Recovering 3D

• Triangulation

• Tracking– image matching

– triangulation (several cameras)

6

Optical body tracking: practice

• 20-30 markers

• Points of interest– hips, elbows, knees,...

– head (3 markers)

• Images are postprocessed (tracking)

• 100-250 Hz

Advantages of optical capture

• Large active area

• Unemcumbered actor

• Markers are passive

• High enough sampling rates

7

Disadvantages of optical capture

• Cost ($150,00 - 250,000)

• Sensitivity to light

• Sensitivity to reflections

• Marker occlusions

• Tracking time

• Positions only

• Sensitivity to calibration

Digital Poseable MannequinsThe Monkey

• Articulated puppet with joint sensors

• Advantages– easy to use

– easy calibration

– multiple active characters

– cost ($10,000)

• Disadvantages– dynamic realism

8

Datagloves

• Track the hand and fingers

Data processing

• Mapping data to an articulated body– calibration

– body model

– corrections

9

Calibration of the measuring device

• Magnetic sensors– source location (position and orientation)

• Optical trackers– use known objects to compute coefficients

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Calibration of the tracked points

• Relative location wrt object must be estimated

– hand-made measurements

– statistical processing

– skeleton fitting

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10

Skeletton fitting

• Compute the distancesfrom the trackersto thevirtual skeleton

Body model

• Two possible models– one hierarchical articulated body

use joint rotations

– several bodiesuse positions and rotations

11

Hierarchical body

• The model is globally positioned using onebody sensor

• Relative rotations recursively define thepositions of the links

Relative rotations

• Measure rotations wrt the world

• Deduce relative rotations

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12

Advantages and drawbacks ofhierarchical skeletons

• Advantages– simplicity: compute and apply relative rotations

– the body is always connected

• Drawbacks– accumulation of error

Sources of errors

• Magnetic sensors

• Calibration

• Trackers not rigidly fixed

13

Several-body model

• Drive body, forearms and tibias wrt world

Difficulties• Wrong data results in constraint violation

• Inverse kinematics is sensitive tosingularities

release constraints, apply optimization

14

Mapping to a different body

• Use optimization– positions

– orientations

– limit motion

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Summary

• Variety of techniques

• Data correction is necessary

• Remaining problems:– noisy data

– foot slippery

15

References

• Molet, Boulic, Thalmann,A real-time converter for humanmotion capture, Eurographics Workshop on ComputerAnimation and Simulation, Springer-Verlag, Wien, 1996

• Bodenheimer, Rose,The process of motion capture:dealing with the data, Eurographics Workshop onComputer Animation and Simulation, Springer-Verlag,Wien, 1997

• http://reality.sgi.com/jam_sb/mocap/MoCapWP_v2.0.html