Article

An efficient search algorithm for motion data using weighted PCA

Authors:

E. FiumeAuthors Info & Claims

SCA '05: Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation

Pages 67 - 76

https://doi.org/10.1145/1073368.1073377

Published: 29 July 2005 Publication History

Abstract

Good motion data is costly to create. Such an expense often makes the reuse of motion data through transformation and retargetting a more attractive option than creating new motion from scratch. Reuse requires the ability to search automatically and efficiently a growing corpus of motion data, which remains a difficult open problem. We present a method for quickly searching long, unsegmented motion clips for subregions that most closely match a short query clip. Our search algorithm is based on a weighted PCA-based pose representation that allows for flexible and efficient pose-to-pose distance calculations. We present our pose representation and the details of the search algorithm. We evaluate the performance of a prototype search application using both synthetic and captured motion data. Using these results, we propose ways to improve the application's performance. The results inform a discussion of the algorithm's good scalability characteristics.

References

[1]

{AFO03} Arikan O., Forsyth D. A., O'Brien J. F.: Motion synthesis from annotations. ACM Trans. Graph. 22, 3 (2003), 402--408.

Digital Library

[2]

{AMN*94} Arya S., Mount D. M., Netanyahu N. S., Silverman R., Wu A.: An optimal algorithm for approximate nearest neighbor searching. In SODA '94: Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms (1994), Society for Industrial and Applied Mathematics, pp. 573--582.

Digital Library

[3]

{Bis96} Bishop C. M.: Neural networks for pattern recognition. Oxford University Press, Oxford, UK, UK, 1996.

Digital Library

[4]

{BSP*04} Barbic J., Safonova A., Pan J.-Y., Faloutsos C., Hodgins J. K., Pollard N. S.: Segmenting motion capture data into distinct behaviors. In GI '04: Proceedings of the 2004 conference on Graphics interface (2004), Canadian Human-Computer Communications Society, pp. 185--194.

Digital Library

[5]

{BW95} Bruderlin A., Williams L.: Motion signal processing. In SIGGRAPH (1995), pp. 97--104.

Digital Library

[6]

{CBA*96} Campbell L. W., Becker D. A., Azarbayejani A., Bobick A. F., Pentland A.: Invariant features for 3-d gesture recognition. In FG '96: Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96) (1996), IEEE Computer Society, p. 157.

Digital Library

[7]

{CKHP02} Chu S., Keogh E. J., Hart D., Pazzani M. J.: Iterative deepening dynamic time warping for time series. In SDM (2002).

[8]

{CVB*03} Cardle M., Vlachos M., Brooks S., Keogh E., Gunopulos D.: Fast motion capture matching with replicated motion editing. In SIGGRAPH 2003, Sketches and Applications (jul 2003), ACM Press.

[9]

{GBT04} Glardon P., Boulic R., Thalmann D.: Pca-based walking engine using motion capture data. In Computer Graphics International (2004), pp. 292--298.

Digital Library

[10]

{Gra98} Grassia F. S.: Practical parameterization of rotations using the exponential map. J. Graph. Tools 3, 3 (1998), 29--48.

Digital Library

[11]

{HRS94} Hollars M. G., Rosenthal D. E., Sherman M. A.: SD Fast User's Manual, 1994.

[12]

{JFS95} Jacobs C. E., Finkelstein A., Salesin D. H.: Fast multiresolution image querying. In SIGGRAPH '95: Proceedings of the 22nd annual conference on Computer graphics and interactive techniques (New York, NY, USA, 1995), ACM Press, pp. 277--286.

Digital Library

[13]

{Joh03} Johnson M. P.: Exploiting Quaternions to Support Expressive Interactive Character Motion. PhD thesis, Massachusettes Institute of Technology, 2003.

[14]

{KG03} Kovar L., Gleicher M.: Flexible automatic motion blending with registration curves. In SCA '03: Proceedings of the 2003 ACM SIGGRAPH/Eurographics Symposium on Computer animation (Aire-la-Ville, Switzerland, Switzerland, 2003), Eurographics Association, pp. 214--224.

Digital Library

[15]

{KG04} Kovar L., Gleicher M.: Automated extraction and parameterization of motions in large data sets. ACM Trans. Graph. 23, 3 (2004), 559--568.

Digital Library

[16]

{KGP02} Kovar L., Gleicher M., Pighin F.: Motion graphs, 2002.

[17]

{KP99} Keogh E. J., Pazzani M. J.: Scaling up dynamic time warping to massive dataset. In PKDD '99: Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery (London, UK, 1999), Springer-Verlag, pp. 1--11.

Digital Library

[18]

{KPZ*04} Keogh E., Palpanas T., Zordan V., Gunopulos D., Cardle M.: Indexing large human-motion databases. In VLDB 2004 (2004).

Digital Library

[19]

{LWS02} Li Y., Wang T., Shum H.-Y.: Motion texture: a two-level statistical model for character motion synthesis. In SIGGRAPH '02: Proceedings of the 29th annual conference on Computer graphics and interactive techniques (New York, NY. USA, 2002), ACM Press, pp. 465--472.

Digital Library

[20]

{McC94} McCloud S.: Understanding Comics. Perennial Currents, 1994.

[21]

{MKP02} Martínez J. M., Koenen R., Pereira F.: Mpeg-7: the generic multimedia content description standard. IEEE Computer Society (2002), 78--87.

Digital Library

[22]

{Mou05} Mount D. M.: ANN Programming Manual, 2005.

[23]

{NF04} Neff M., Fiume E.: Methods for exploring expressive stance. In SCA '04: Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation (New York, NY, USA, 2004), ACM Press, pp. 49--58.

Digital Library

[24]

{PG04} P. Glardon R. Boulic D. T.: A coherent locomotion engine extrapolating beyond experimental data. In CASA 2004 Proceedings (2004).

[25]

{Row98} Roweis S.: Em algorithms for pca and spca. In NIPS '97: Proceedings of the 1997 conference on Advances in neural information processing systems 10 (1998), MIT Press, pp. 626--632.

Digital Library

[26]

{SL02} Skočaj D., Leonardis A.: Weighted incremental subspace learning. In Workshop on Cognitive Vision, proceedings (Zurich, Switzerland, September 19--20 2002).

[27]

{vHB01} Von Hardenberg C., Brard F.: Bare-hand humancomputer interaction. In Proceedings of Perceptual User Interfaces, 2001. (2001).

Digital Library

[28]

{VKG02} Vlachos M., Kollios G., Gunopulos D.: Discovering similar multidimensional trajectories. In In Proc. of 18th ICDE, San Jose, p. 673--684, CA, 2002. (2002).

Digital Library

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Index Terms

An efficient search algorithm for motion data using weighted PCA
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation

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cover image ACM Conferences

SCA '05: Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation

July 2005

366 pages

ISBN:1595931988

DOI:10.1145/1073368

Conference Chairs:
Demetri Terzopoulos
New York University, USA
,
Victor Brian Zordan
University of California at Riverside, USA
,
Program Chairs:
Ken Anjyo
OLM Digital, Inc., Japan
,
Petros Faloutsos
University of California at Los Angeles, USA

Copyright © 2005 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]

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
EUROGRAPHICS: The European Association for Computer Graphics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 July 2005

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SCA05

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SIGGRAPH
EUROGRAPHICS

SCA05: Symposium on Computer Animation

July 29 - 31, 2005

California, Los Angeles

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https://doi.org/10.3390/s24113507
Goo J(2024)Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion Maps2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825109(2949-2957)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825109
Priya MGlory HSriram V(2024)Enhanced Deep Learning for IIoT Threat Intelligence: Revealing Advanced Persistent Threat Attack PatternsApplications and Techniques in Information Security10.1007/978-981-97-9743-1_15(201-217)Online publication date: 3-Nov-2024
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