Post on 13-Jul-2020
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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
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Capture harware
• Magnetic sensors
• Optical capture
• Rotation encoders (puppet)
Magnetic sensors
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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
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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
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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)
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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
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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
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Datagloves
• Track the hand and fingers
Data processing
• Mapping data to an articulated body– calibration
– body model
– corrections
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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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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
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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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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
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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
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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
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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