Abstract
Large human motion databases contain variants of natural motions that are valuable for animation generation and synthesis. But retrieving visually similar motions is still a difficult and time-consuming problem. This paper provides methods for identifying visually and numerically similar motions in a large database given a query of motion segment. We propose an efficient indexing strategy that represents the motions compactly through a preprocessing. This representation scales down the range of searching the database. Motions in this range are possible candidates of the final matches. For detailed comparisons between the query and the candidates, we propose an algorithm that compares the motions’ curves swiftly. Our methods can apply to large human motion databases and achieve high performance and accuracy compared with previous work. We present experimental results on testing a database of about 2.9 million frames, or about 27 hours of motions played at 30 Hz.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kovar, L., Gleicher, M.: Automated extraction and parameterization of motions in large data sets. In: Proceedings of ACM SIGGRAPH 2004, pp. 559–568 (2004)
Muller, M., Roder, T., Glausen, M.: Efficient content-based retrieval of motion capture data. In: Proceedings of ACM SIGGRAPH 2005, pp. 677–685 (2005)
Liu, F., Zhuan, Y., Wu, F., Pan, Y.: 3d motion retrieval with motion index tree. Computer Vision and Image Understanding 92, 265–284 (2003)
Graphics Lab, Carnegie-Mellon University (Carnegie-Mellon MoCap Database), http://mocap.cs.cmu.edu
Witten, I.H., Moffat, A., Bell, T.C.: Managing Gigabytes. Morgan Kaufmann Publishers, San Francisco (1999)
Bakker, E.M., Lew, M., Huang, T.S., Sebe, N., Zhou, X.S. (eds.): CIVR 2003. LNCS, vol. 2728. Springer, Heidelberg (2003)
Clausen, M., Kurth, F.: A unified approach to content-based and fault tolerant music recognition. IEEE Transactions on Multimedia 6, 717–731 (2004)
Faloutsos, C., Ranganathan, M., Manolopoulos, Y.: Fast subsequence matching in time-series databases. In: Proceedings of 1994 ACM SIGMOD International Conference on Management of Data, pp. 419–429 (1994)
Agrawal, R., Faloutsos, C., Swami, A.: Efficient similarity search in sequence databases. In: Lomet, D.B. (ed.) FODO 1993. LNCS, vol. 730, pp. 69–84. Springer, Heidelberg (1993)
Chan, K., Fu, W.: Efficient time series matching by wavelets. In: Proceedings of the 15th IEEE International Conference on Data Engineering, pp. 126–133 (1999)
Keogh, E., Chakrabarti, K., Mehrotra, S., Pazzani, M.: Locally adaptive dimensionality reduction for indexing large time series databases. In: Proceedings of 1994 ACM SIGMOD International Conference on Management of Data, pp. 151–162 (2001)
Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: Proceedings of 1994 ACM SIGMOD International Conference on Management of Data, pp. 47–57 (1984)
Vlachos, M., Hadjieleftheriou, M., Gunopulos, D., Keogh, E.: Indexing multi-dimensional time-series with support for multiple distance measures. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 216–225 (2003)
Lee, J., Chai, J., Reitsma, P., Hodgins, J., Pollard, N.: Interactive control of avatars animated with human motion data. In: Proceedings of ACM SIGGRAPH 2002, pp. 491–500 (2002)
Arikan, O., Forsyth, D.A.: Interactive motion generation from examples. In: Proceedings of ACM SIGGRAPH 2002, pp. 483–490 (2002)
Wang, J., Bodenheimer, B.: An evaluation of a cost metric for selecting transitions between motion segments. In: Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2003, pp. 232–238 (2003)
Brejova, B., Brown, D., Vinar, T.: Vector seeds: An extension to spaced seeds. Journal of Computer and System Sciences 70, 364–380 (2005)
Ma, B., Tromp, J., Li, M.: Patternhunter: faster and more sensitive homology search. Bioinformatics 18, 440–445 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lin, Y. (2006). Efficient Motion Search in Large Motion Capture Databases. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_16
Download citation
DOI: https://doi.org/10.1007/11919476_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48628-2
Online ISBN: 978-3-540-48631-2
eBook Packages: Computer ScienceComputer Science (R0)