skip to main content
10.1145/1268517.1268568acmotherconferencesArticle/Chapter ViewAbstractPublication PagesgiConference Proceedingsconference-collections
Article

Adapting wavelet compression to human motion capture clips

Published: 28 May 2007 Publication History

Abstract

Motion capture data is an effective way of synthesizing human motion for many interactive applications, including games and simulations. A compact, easy-to-decode representation is needed for the motion data in order to support the real-time motion of a large number of characters with minimal memory and minimal computational overheads. We present a wavelet-based compression technique that is specially adapted to the nature of joint angle data. In particular, we define wavelet coefficient selection as a discrete optimization problem within a tractable search space adapted to the nature of the data. We further extend this technique to take into account visual artifacts such as footskate. The proposed techniques are compared to standard truncated wavelet compression and principal component analysis based compression. The fast decompression times and our focus on short, recomposable animation clips make the proposed techniques a realistic choice for many interactive applications.

References

[1]
O. Arikan. Compression of motion capture databases. In SIGGRAPH'06, pages 890--897, 2006.
[2]
J. Assa, Y. Caspi, and D. Cohen-Or. Action synopsis: Pose selection and illustration. In SIGGRAPH'05, pages 667--676, 2005.
[3]
J. Barbicč, A. Safonova, J.-Y. Pan, C. Faloutsos, J. K. Hodgins, and N. S. Pollard. Segmenting motion capture data into distinct behaviors. In Graphics Interface, pages 185--194, 2004.
[4]
H. M. Briceño, P. V. Sander, L. McMillan, S. Gortler, and H. Hoppe. Geometry videos: A new representation for 3D animations. In Symp. Computer Animation, pages 136--146, 2003.
[5]
J. Chai and J. K. Hodgins. Performance animation from low-dimensional control signals. In SIGGRAPH'05, pages 686--696, 2005.
[6]
CMU graphics lab motion capture database. mocap.cs.cmu.edu, April 2006.
[7]
K. Forbes and E. Fiume. An efficient search algorithm for motion data using weighted PCA. In Symp. Computer Animation, pages 67--76, 2005.
[8]
P. Glardon, R. Boulic, and D. Thalmann. A coherent locomotion engine extrapolating beyond experimental data. In Computer Animation and Social Agents, pages 73--84, 2004.
[9]
K. Grochow, S. L. Martin, A. Hertzmann, and Z. Popović. Style-based inverse kinematics. In SIGGRAPH'04, pages 522--531, 2004.
[10]
L. Ikemoto, O. Arikan, and D. Forsyth. Knowing when to put your foot down. In Symp. Interactive 3D Graphics and Games, pages 49--53, 2006.
[11]
K. Kondo and K. Matsuda. Keyframes extraction method for motion capture data. Journal for Geometry and Graphics, 8(1):81--90, 2004.
[12]
J. Lee and S. Y. Shin. A hierarchical approach to interactive motion editing for human-like figures. In SIGGRAPH'99, pages 39--48, 1999.
[13]
J. Lee and S. Y. Shin. Multiresolution motion analysis with applications. In Intl Workshop on Human Modeling and Animation, pages 131--143, 2000.
[14]
I. S. Lim and D. Thalmann. Key-posture extraction out of human motion data by curve simplification. In Intl Conf IEEE Engineering in Medicine and Biology Society, volume 2, pages 1167--1169, 2001.
[15]
G. Liu and L. McMillan. Segment-based human motion compression. In Symp. Computer Animation, pages 127--135, 2006.
[16]
Z. Liu, S. J. Gortler, and M. F. Cohen. Hierarchical spacetime control. In SIGGRAPH'94, pages 35--42, 1994.
[17]
K. Pullen and C. Bregler. Motion capture assisted animation: Texturing and synthesis. In SIGGRAPH'02, pages 501--508, 2002.
[18]
A. Safonova, J. K. Hodgins, and N. S. Pollard. Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces. In SIGGRAPH'04, pages 514--521, 2004.
[19]
W. Sweldens. The lifting scheme: A construction of second generation wavelets. SIAM Journal on Mathematical Analysis, 29(2):511--546, 1998.
[20]
C. Welman. Inverse kinematics and geometric constraints for articulated figure manipulation. Master's thesis, Simon Fraser University, 1993.
[21]
J. Ziv and A. Lempel. Compression of individual sequences via variable-rate coding. IEEE Transactions on Information Theory, 24:530--536, 1978.

Cited By

View all
  • (2024)A Unified Diffusion Framework for Scene-aware Human Motion Estimation from Sparse Signals2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.02008(21251-21262)Online publication date: 16-Jun-2024
  • (2023)3D Human Motion Data Compression Based on Computer Vision2023 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)10.1109/ICICML60161.2023.10424871(725-729)Online publication date: 3-Nov-2023
  • (2023)Embedded Deformation-based Compression for Human 3D Dynamic Meshes with Changing Topology2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)10.1109/ICCVW60793.2023.00239(2244-2254)Online publication date: 2-Oct-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
GI '07: Proceedings of Graphics Interface 2007
May 2007
352 pages
ISBN:9781568813370
DOI:10.1145/1268517
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

  • CHCCS: The Canadian Human-Computer Communications Society

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 May 2007

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. IK correction
  2. compression
  3. skeletal animation
  4. wavelet

Qualifiers

  • Article

Acceptance Rates

Overall Acceptance Rate 206 of 508 submissions, 41%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)9
  • Downloads (Last 6 weeks)2
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)A Unified Diffusion Framework for Scene-aware Human Motion Estimation from Sparse Signals2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.02008(21251-21262)Online publication date: 16-Jun-2024
  • (2023)3D Human Motion Data Compression Based on Computer Vision2023 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)10.1109/ICICML60161.2023.10424871(725-729)Online publication date: 3-Nov-2023
  • (2023)Embedded Deformation-based Compression for Human 3D Dynamic Meshes with Changing Topology2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)10.1109/ICCVW60793.2023.00239(2244-2254)Online publication date: 2-Oct-2023
  • (2023)PhaseMP: Robust 3D Pose Estimation via Phase-conditioned Human Motion Prior2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01353(14679-14691)Online publication date: 1-Oct-2023
  • (2020)Motion Recurring Pattern Analysis: A Lossless Representation for Motion Capture DatabasesIEEE Access10.1109/ACCESS.2020.29894308(78932-78941)Online publication date: 2020
  • (2019)A Survey on Motion Capture Data Compression AlgorithmProceedings of the 2nd International Conference on Big Data Technologies10.1145/3358528.3358577(19-23)Online publication date: 28-Aug-2019
  • (2017)Multiresolution coding of motion capture data for real-time multimedia applicationsMultimedia Tools and Applications10.5555/3124201.312423476:15(16683-16698)Online publication date: 1-Aug-2017
  • (2017)Online MoCap Data Coding With Bit Allocation, Rate Control, and Motion-Adaptive Post-ProcessingIEEE Transactions on Multimedia10.1109/TMM.2017.265542319:6(1127-1141)Online publication date: 1-Jun-2017
  • (2017)Modeling and compression of motion capture data2017 Learning and Technology Conference (L&T) - The MakerSpace: from Imagining to Making!10.1109/LT.2017.8088120(7-13)Online publication date: Feb-2017
  • (2017)A human motion feature based on semi-supervised learning of GMMMultimedia Systems10.1007/s00530-014-0429-223:1(85-93)Online publication date: 1-Feb-2017
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media