Human Motion Variation Synthesis with Multivariate Gaussian Processes

Liuyang Zhou, Lifeng Shang, Hubert P. H. Shum and Howard Leung
Computer Animation and Virtual Worlds (CAVW) - Proceedings of the 2014 International Conference on Computer Animation and Social Agents (CASA), 2014

Impact Factor: 1.010# Citation: 6##

Human Motion Variation Synthesis with Multivariate Gaussian Processes
# Impact factors from the Journal Citation Reports 2021
## Citation counts from Google Scholar as of 2022

Abstract

Human motion variation synthesis is important for crowd simulation and interactive applications to enhance synthesis quality. In this paper, we propose a novel generative probabilistic model to synthesize variations of human motion. Our key idea is to model the conditional distribution of each joint via a multivariate Gaussian process model, namely semi-parametric latent factor model (SLFM). SLFM can effectively model the correlations between degrees of freedom (DOFs) of joints rather than dealing with each DOF separately as implemented in existing methods. A detailed evaluation is performed to show that the proposed approach can effectively synthesize variations of different types of motions. Motions generated by our method show a richer variation compared with existing ones. Finally, our user study shows that the synthesized motion has a similar level of naturalness to captured human motions. Our method is best applied in computer games and animations to introduce motion variations.

Downloads

YouTube

Citations

BibTeX

@article{zhou14human,
 author={Zhou, Liuyang and Shang, Lifeng and Shum, Hubert P. H. and Leung, Howard},
 journal={Computer Animation and Virtual Worlds},
 title={Human Motion Variation Synthesis with Multivariate Gaussian Processes},
 year={2014},
 volume={25},
 number={3--4},
 pages={301--309},
 numpages={9},
 doi={10.1002/cav.1599},
 publisher={John Wiley and Sons Ltd.},
 Address={Chichester, UK},
}

RIS

TY  - JOUR
AU  - Zhou, Liuyang
AU  - Shang, Lifeng
AU  - Shum, Hubert P. H.
AU  - Leung, Howard
T2  - Computer Animation and Virtual Worlds
TI  - Human Motion Variation Synthesis with Multivariate Gaussian Processes
PY  - 2014
VL  - 25
IS  - 3--4
SP  - 301
EP  - 309
DO  - 10.1002/cav.1599
PB  - John Wiley and Sons Ltd.
ER  - 

Plain Text

Liuyang Zhou, Lifeng Shang, Hubert P. H. Shum and Howard Leung, "Human Motion Variation Synthesis with Multivariate Gaussian Processes," Computer Animation and Virtual Worlds, vol. 25, no. 3--4, pp. 301-309, John Wiley and Sons Ltd., 2014.

Similar Research

Edmond S. L. Ho, Hubert P. H. Shum, He Wang and Li Yi, "Synthesizing Motion with Relative Emotion Strength", Proceedings of the 2017 ACM SIGGRAPH Asia Workshop on Data-Driven Animation Techniques (D2AT), 2017
Hubert P. H. Shum, Taku Komura and Pranjul Yadav, "Angular Momentum Guided Motion Concatenation", Computer Animation and Virtual Worlds (CAVW) - Proceedings of the 2009 International Conference on Computer Animation and Social Agents (CASA), 2009
Hubert P. H. Shum, Ludovic Hoyet, Edmond S. L. Ho, Taku Komura and Franck Multon, "Preparation Behaviour Synthesis with Reinforcement Learning", Proceedings of the 2013 International Conference on Computer Animation and Social Agents (CASA), 2013
He Wang, Edmond S. L. Ho, Hubert P. H. Shum and Zhanxing Zhu, "Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling", IEEE Transactions on Visualization and Computer Graphics (TVCG), 2021
Hubert P. H. Shum, Ludovic Hoyet, Edmond S. L. Ho, Taku Komura and Franck Multon, "Natural Preparation Behavior Synthesis", Computer Animation and Virtual Worlds (CAVW), 2013

 

 
 

Last updated on 25 September 2022, RSS Feeds