Summary & Homework
Jinxiang Chai
Outline
Motion data process paper summary
Presentation tips
Homework
Paper assignment
Skeleton Model Extraction
Estimate the skeleton model from motion capture data
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
• Motion edit (can satisfy user constraints and fast)
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
• Motion edit (can satisfy user constraints and fast)
However: does not work for many user-defined constraints
does not utilize spatial-temporal correlation in human motion
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
• Motion edit (can satisfy user constraints and fast)
• Expression cloning (facial data) (cannot satisfy user constraints)
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
• Motion edit (can satisfy user constraints and fast)
• Expression cloning (facial data) (cannot satisfy user constraints)
• Motion synopsis
Motion Data Processing I
Operations on single motion sequence
• Motion warping (cannot satisfy user constraints)
• Motion retargeting (can satisfy user constraints but slow)
• Motion edit (can satisfy user constraints and fast)
• Expression cloning (facial data) (cannot satisfy user constraints)
• Motion synopsis
• What else?
Motion Data Processing I
Operations on single motion sequence
• Motion segmentation?
• Motion recognition?
• Motion filtering?
• More operations in facial data
Motion Data Processing II
Operations between two motion sequence
• Motion style translation
• What else?
Motion Data Processing II
Operations between two motion sequence
• Motion style translation
• What else?
Motion Data Processing II
Operations between two motion sequence
• Motion style translation
• Motion interpolation?
Motion Data Processing III
Operations on multiple motion sequences/database
• Motion data compression
Motion Data Processing III
Operations on multiple motion sequences/database
• Motion data compression
• What else?
Motion Data Processing III
Operations on multiple motion sequences/database
• Motion data compression
• Motion Retrieval?
• Motion synthesis?
Presentation Tips
Choose right background• Use blue or black or dark colors
Focus on important things• Always talk about what, why, and how
• Detailize the most important technical content
• Always talk about the limitations of the paper
How to deal with equations• Avoid using too many equations
• Talk about the intuition of the equations
• Explain each term of the equations
Presentation Tips (Cont.)
Choose the right background• Use dark colors (blue or black)
Be consistent• Font type, size, color, bullets, figure captions etc.
Use short & concise sentences• Do not copy & paste from the paper
• Use images, diagrams, figures, videos to demonstrate ideas
Presentation Tips (Cont.)
Play videos• Explain each video
• Move the mouse away from the window
Example Slides
Goal: everyone can generate and control human motion easily and quickly
Online animation control
Interfaces for Controlling Human Motion
Applications: Online Animation
Performance-based facial animation for home use
Tiger Woods PGA Tour 2005
Mike Tyson Heavyweight Boxing
Friday Night 3D Bowling
Teleconferencing (from BT)
Xbox Outlaw Tennis
Multi-user Virtual Worlds
Virtual Poker Room
Virtual Presenter
Reordering motion clip [Lee et al. SIG02, Kovar et al. SIG02, Pullen & Bregler SIG02, Arikan et al. SIG03]
Learning model from human motion [Brand & Hertzmann SIG00, Li et al. SIG02]
Interpolating motions [Rose et al. CG&A98, Kovar et al. SIG04]
Animation from Mocap Data
Video Analysis
Overview
Online motion synthesis
Online local modeling
Low-dimensional control signals
Preprocessedmotion capture
dataPreprocessed
motion capturedata
Online local models
Online Motion Optimization
2
21
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Tt
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t
Optimizing a nonlinear function in about 7 dimensional space wt :
Control term
Smoothness term
Pose prior term
1~q tq
~
tc~…
…
1~c
?
Outline
Motion data paper summary
Presentation tips
Homework
Paper assignment
Dimensionality reduction using PCA
tttt wUpq ~Current pose Mean pose
Eigen-poses Low-dimensional space
Linear model:
Mean pose
Eigen-poses
Dim(wt)?
Linear Dimensionality Reduction
Linear Dimensionality Reduction
0 5 10 15 20 25 30 35 40 45 500
5
10
15
20
25
30
Ave
rage
rec
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stru
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A large heterogeneous database (1 hour of data)
PCA (38D for error<1o)
Number of dimensions
Reconstruction Error Curve
0 10 20 30 40 50 600
0.5
1
1.5
2
2.5
Ave
rage
rec
on
stru
ctio
n e
rro
r(d
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e p
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A large database
Number of dimensions of Wt
tttt wUpq ~
Minimal Dimensionality
0 10 20 30 40 50 600
0.5
1
1.5
2
2.5
Ave
rage
rec
on
stru
ctio
n e
rro
r(d
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A large database
Number of dimensions of Wt
tttt wUpq ~
7
0.8
tttt wUpq ~
56 dim 7 dim
Videos
Two Animation videos rendered by Maya• Original mocap sequence
• Reconstructed mocap sequence
Startup Codes & Data
Motion capture data (.amc files and .asf file)
A skinned character model
Visualize amc/asf file• Read asf/amc file
• Visualize mocap data
• Forward kinematics
Matlab codes• Read and write .amc file
Softwares
Maya• To be installed in Rm 220, HRBB
• Render each frame based on mocap data and character model
• Instruction on how to render animation
Adobe Premier • Installed in Rm 220, HRBB
• Making video from image sequences
Outline
Motion data paper summary
Presentation tips
Homework
Paper assignment