Article

Parametric motion graphs

Authors:

Michael GleicherAuthors Info & Claims

I3D '07: Proceedings of the 2007 symposium on Interactive 3D graphics and games

Pages 129 - 136

https://doi.org/10.1145/1230100.1230123

Published: 30 April 2007 Publication History

Abstract

In this paper, we present an example-based motion synthesis technique that generates continuous streams of high-fidelity, controllable motion for interactive applications, such as video games. Our method uses a new data structure called a parametric motion graph to describe valid ways of generating linear blend transitions between motion clips dynamically generated through parametric synthesis in realtime. Our system specifically uses blending-based parametric synthesis to accurately generate any motion clip from an entire space of motions by blending together examples from that space. The key to our technique is using sampling methods to identify and represent good transitions between these spaces of motion parameterized by a continuously valued parameter. This approach allows parametric motion graphs to be constructed with little user effort. Because parametric motion graphs organize all motions of a particular type, such as reaching to different locations on a shelf, using a single, parameterized graph node, they are highly structured, facilitating fast decision-making for interactive character control. We have successfully created interactive characters that perform sequences of requested actions, such as cartwheeling or punching.

References

[1]

Allen, B., Curless, B., and Popovic, Z. 2002. Articulated body deformation from range scan data. ACM Transactions on Graphics.

Digital Library

[2]

Arikan, O., and Forsythe, D. A. 2002. Interactive motion generation from examples. ACM Transactions on Graphics.

Digital Library

[3]

Arikan, O., Forsyth, D. A., and O'Brien, J. 2003. Motion synthesis from annotations. ACM Transactions on Graphics.

Digital Library

[4]

Bruderlin, A., and Williams, L. 1995. Motion signal processing. In ACM SIGGRAPH.

Digital Library

[5]

Gleicher, M., Shin, H. J., Kovar, L., and Jepsen, A. 2003. Snap-together motion: Assembling run-time animation. In ACM SIGGRAPH Symposium on Interactive 3D Graphics.

Digital Library

[6]

Hodgins, J., W. Wooten, Brogan, D., and O'Brien, J. 1995. Animating human athletics. In ACM SIGGRAPH.

Digital Library

[7]

Kim, T., Park, S., and Shin, S. 2003. Rhythmic-motion synthesis based on motion-beat analysis. ACM Transactions on Graphics.

Digital Library

[8]

Kovar, L., and Gleicher, M. 2004. Automated extraction and parameterization of motions in large data sets. ACM Transactions on Graphics.

Digital Library

[9]

Kovar, L., Gleicher, M., and Pighin, F. 2002. Motion graphs. ACM Transactions on Graphics.

Digital Library

[10]

Kwon, T., and Shin, S. Y. 2005. Motion modeling for on-line locomotion synthesis. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[11]

Lamouret, A., and van de Panne, M. 1996. Motion synthesis by example. In Eurographics workshop on Computer animation and simulation.

Digital Library

[12]

Lee, J., and Lee, K. H. 2004. Precomputing avatar behavior from human motion data. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[13]

Lee, J., Chai, J., Reitsma, P., Hodgins, J., and Pollard, N. 2002. Interactive control of avatars animated with human motion data. ACM Transactions on Graphics.

Digital Library

[14]

Mizuguchi, M., Buchanan, J., and Calvert, T. 2001. Data driven motion transitions. In Eurographics Short Presentations.

[15]

Mukai, T., and Kuriyama, S. 2005. Geostatistical motion interpolation. In ACM SIGGRAPH.

Digital Library

[16]

Park, S. I., Shin, H. J., and Shin, S. Y. 2002. On-line locomotion generation based on motion blending. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[17]

Perlin, K., and Goldberg, A. 1996. Improv: A system for scripting interactive actors in virtual worlds. In ACM SIGGRAPH.

Digital Library

[18]

Perlin, K. 1995. Real time responsive animation with personality. IEEE Transactions on Visualization and Computer Graphics.

Digital Library

[19]

Reitsma, P. S. A., and Pollard, N. S. 2004. Evaluating motion graphs for character navigation. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[20]

Rose, C., Guenter, B., Bodenheimer, B., and Cohen, M. 1996. Efficient generation of motion transitions using spacetime constraints. In ACM SIGGRAPH.

Digital Library

[21]

Rose, C., Cohen, M., and Bodenheimer, B. 1998. Verbs and adverbs: multidimensional motion interpolation. IEEE CG&A.

Digital Library

[22]

Schödl, A., Szeliski, R., Salesin, D. H., and Essa, I. 2000. Video textures. In ACM SIGGRAPH.

Digital Library

[23]

Shin, H. J., and Oh, H. S. 2006. Fat graphs: Constructing an interactive character with continuous controls. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[24]

Srinivasan, M., Metoyer, R. A., and Mortensen, E. N. 2005. Controllable character animation using mobility maps. Graphics Interface.

Digital Library

[25]

Sun, H., and Metaxas, D. 2001. Automating gait animation. In ACM SIGGRAPH.

Digital Library

[26]

Sung, M., Kovar, L., and Gleicher, M. 2005. Fast and accurate goal-directed motion synthesis for crowds. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation.

Digital Library

[27]

Wiley, D., and Hahn, J. 1997. Interpolation synthesis of articulated figure motion. IEEE CG&A.

Digital Library

Cited By

Egan DJovane ASzkaradek JFletcher GCosker DMcDonnell R(2024)Dog Code: Human to Quadruped Embodiment using Shared CodebooksProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696339(1-11)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696339
Chu YYang Z(2024)Real-time Diverse Motion In-betweening with Space-time ControlProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696327(1-8)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696327
Jovane AEgan DVargas MMythen SMcDonnell R(2024)Virtual Animal Embodiment for Actor Training2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW62533.2024.00083(428-431)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VRW62533.2024.00083
Show More Cited By

Index Terms

Parametric motion graphs
1. Computing methodologies
  1. Computer graphics
    1. Animation

Recommendations

Snap-together motion: assembling run-time animations
I3D '03: Proceedings of the 2003 symposium on Interactive 3D graphics

Many virtual environments and games must be populated with synthetic characters to create the desired experience. These characters must move with sufficient realism, so as not to destroy the visual quality of the experience, yet be responsive, ...
Snap-together motion: assembling run-time animations
SIGGRAPH '08: ACM SIGGRAPH 2008 classes

Many virtual environments and games must be populated with synthetic characters to create the desired experience. These characters must move with sufficient realism, so as not to destroy the visual quality of the experience, yet be responsive, ...
Motion graphs
SIGGRAPH '02: Proceedings of the 29th annual conference on Computer graphics and interactive techniques

In this paper we present a novel method for creating realistic, controllable motion. Given a corpus of motion capture data, we automatically construct a directed graph called a motion graph that encapsulates connections among the database. The motion ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

I3D '07: Proceedings of the 2007 symposium on Interactive 3D graphics and games

April 2007

196 pages

ISBN:9781595936288

DOI:10.1145/1230100

General Chairs:
Bruce Gooch
Northwestern University
,
Peter-Pike Sloan
Microsoft
,
Program Chairs:
Jonathan Cohen
Lawrence Livermore National Laboratory
,
Greg Turk
Georgia Institute of Technology
,
Ben Watson
North Carolina State University

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 April 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

I3D07

Sponsor:

SIGGRAPH

I3D07: Symposium on Interactive 3D Graphics and Games 2007

April 30 - May 2, 2007

Washington, Seattle

Acceptance Rates

Overall Acceptance Rate 148 of 485 submissions, 31%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

187
Total Citations
View Citations
1,157
Total Downloads

Downloads (Last 12 months)37
Downloads (Last 6 weeks)4

Reflects downloads up to 10 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Egan DJovane ASzkaradek JFletcher GCosker DMcDonnell R(2024)Dog Code: Human to Quadruped Embodiment using Shared CodebooksProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696339(1-11)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696339
Chu YYang Z(2024)Real-time Diverse Motion In-betweening with Space-time ControlProceedings of the 17th ACM SIGGRAPH Conference on Motion, Interaction, and Games10.1145/3677388.3696327(1-8)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3677388.3696327
Jovane AEgan DVargas MMythen SMcDonnell R(2024)Virtual Animal Embodiment for Actor Training2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW62533.2024.00083(428-431)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VRW62533.2024.00083
Xia GXue PZhang DLiu QSun Y(2024)A Deep Learning Framework for Start–End Frame Pair-Driven Motion SynthesisIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.321359635:5(7021-7034)Online publication date: May-2024
https://doi.org/10.1109/TNNLS.2022.3213596
Hácha FDvořák JKáčereková ZVáša L(2024)Editing mesh sequences with varying connectivityComputers and Graphics10.1016/j.cag.2024.103943121:COnline publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.cag.2024.103943
Wang Y(2023)3D Dynamic Image Modeling Based on Machine Learning in Film and Television AnimationJournal of Multimedia Information System10.33851/JMIS.2023.10.1.6910:1(69-78)Online publication date: 30-Mar-2023
https://doi.org/10.33851/JMIS.2023.10.1.69
Tao HHou SZou CBao HXu W(2023)Neural Motion GraphSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618181(1-11)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618181
Egan DCosker DMcDonnell R(2023)NeuroDogProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36069366:3(1-19)Online publication date: 24-Aug-2023
https://dl.acm.org/doi/10.1145/3606936
Kim HCho KHong SNoh J(2023)Recurrent Motion Refiner for Locomotion StitchingComputer Graphics Forum10.1111/cgf.1492042:6Online publication date: 12-Aug-2023
https://doi.org/10.1111/cgf.14920
Ye YLiu LHu LXia S(2023)Neural3Points: Learning to Generate Physically Realistic Full‐body Motion for Virtual Reality UsersComputer Graphics Forum10.1111/cgf.1463441:8(183-194)Online publication date: 20-Mar-2023
https://doi.org/10.1111/cgf.14634
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents