Motion Modeling for Online Locomotion

Synthesis

Taesoo Kwon and Sung Yong Shin

KAIST

Outline

• Motivation

• Related work

• Overview

• Motion analysis

• Motion synthesis

• Conclusions

• Future Work

Motivation

• Real-time locomotion synthesis

• Motion rearrangement : realism

• Motion blending : efficiency and controllability

• Hybrid approach– Locomotive motion generation [PSS02, PSS04]– Rhythmic motion synthesis [KPS03]

• Premise: motion labeling

Related Work

• Motion Segmentation [Bindiganavale & Badler, 1998;Fod et al., 2002;

Kim et al., 2003]

• Motion Classification [Arikan et al., 2003;Kovar & Gleicher, 2004;Forbes & Fiu

me 2005;Mueller & Roeder 2005]

• Motion Labeling for blending [Kim et al., 2003]

Overview

motion specifications

desiredmotion

example motions

motion analysis

hierarchical motion transition graph

motion synthesis

Motion Analysis

• Issues– Motion segmentation

– Motion classification

– Graph construction

• Biomechanical observations– [Per92,Win90]

Biomechanical Observations• Center of mass trajectory

right foot left foot

walk runtransition

COMy

Motion segmentation

• Criteria for motion segmentation– Simple enough for intuitive parameterization

– Long enough to contain motion semantics

– An important motion feature should not be split

Split at every COM peak

Motion Classification

• String encoding–

• Pros– avoid troublesome time-warping

– more robust than numerical computation

M:f

Motion Classification

• Footstep patterns

(a) S (b) R (c) L (d) D (e) F FDLRS , , , ,

Motion Classification

• String Encoding (ideal case)

Motion Classification

• String Encoding (ideal case)

R D L

Motion Classification

• String Encoding (ideal case)

F R F

Motion Classification

• String Encoding (ideal case)

R D L F

Motion Classification

• String Encoding (ideal case)

Refinement

• False peak– Concatenate two motion segments

• Missing peak– Divide a motion segment into two

Graph Construction

Graph Construction

mmmmmmP avftt ,,,,

Motion Analysis Results

• O(n) – 2Ghz PC (AMD 64, 2GB memory)

– For 7.4 min locomotion, about 10 seconds

• Movie

Motion Synthesis

LDR RDL LDRF… …

Motion Synthesis

• Motion specification

• Motion parameter

Motion Sythesis

• How to calculate – Two half cycles in cyclic motion

–

• Regression analysis on

m

RL mm

RL mm

Motion Synthesis

• Motion blending : [PSS04][KG03][ACP02]

• Motion stitching : [GSKJ03]

• Motion retargeting : [SLSG01][KGS02]

Motion Synthesis Result

• 1000+ frames per second

• Movie– Path following

– Online synthesis

Conclusion

• Motion labeling based on string encodings

• Hierarchical motion transition graph

Future work

• Footstep-driven motions such as dancing and boxing