Abstract
This paper presents a framework for efficient content-based motion retrieval. To bridge the gap between user’s vague perception and explicit motion scene description, we propose a Scene Description Language that can translate user’s input into a series of set operations between inverted lists. Our Scene Description Language has three-layer structures, each describing scenes at different levels of granularity. By introducing automatic transition strategy into our retrieval process, our system can search motions that do not exist in a motion database. This property makes our system have potentials to serve as motion synthesis purpose. Moreover, by using various kinds of qualitative features and adaptive segments of motion capture data stream, we obtain a robust clustering that is flexible and efficient for constructing motion graph. Some experimental examples are given to demonstrate the effectiveness and efficiency of proposed algorithms.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Park, S.I., Shin, H.J., Kim, T., Shin, S.Y.: On-line motion blending for real-time locomotion generation. Computer Animation and Virtual Worlds 15(3), 125–138 (2004)
Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. ACM Transactions on Graphics 21(3), 473–482 (2002)
Lee, J., Chai, J., Reitsma, P., Hodgins, J., Pollard, N.: Interactive control of avatars animated with human motion data. ACM Transactions on Graphics 21(3), 491–500 (2002)
CMU. Carnegie-Mellon Mocap Database (2003), http://mocap.cs.cmu.edu
Arikan, O., Forsyth, D.A.: Interactive Motion Generation from Examples. ACM Transactions on Graphics 21(3), 483–490 (2002)
Kovar, L., Gleicher, M.: Automated extraction and parameterization of motions in large data sets. ACM Transactions on Graphics 23(3), 559–568 (2004)
Müller, M., Röder, T., Clausen, M.: Efficient content-based retrieval of motion capture data. ACM Transactions on Graphics 24(3), 677–685 (2005)
Kim, T.H., Park, S.I., Shin, S.Y.: Rhythmic-motion synthesis based on motion-beat analysis. ACM Transactions on Graphics 22(3), 392–401 (2003)
Kwon, T., Shin, S.Y.: Motion modeling for on-line locomotion synthesis. In: Proc. ACM SIGGRAPH/ Eurographics Symposium on Computer Animation, pp. 29–38 (2005)
Chiu, C., Chao, S., Wu, M., Yang, S., Lin, H.: Content-based retrieval for human motion data. Journal of Visual Communication and Image Representation, Special Issue on Multimedia Database Management Systems 15(3), 446–466 (2004)
Liu, F., Zhuang, Y., Wu, F., Pan, Y.: 3D motion retrieval with motion index tree. Computer Vision and Image Understanding 92, 265–284 (2003)
Keogh, E.J., Palpanas, T., Zordan, V.B., Gunopulos, D., Cardle, M.: Indexing large human-motion databases. In: Proc. 30th VLDB Conf., pp. 780–791 (2004)
Müller, M., Röder, T., Clausen, M.: Efficient Indexing And Retrieval of Motion Capture Data Based on Adaptive Segmentation. In: Proceedings of the 4th Intl. Workshop on Content-Based Multimedia Indexing, Riga, Latvia (2005)
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
Gao, Y., Ma, L., Chen, Y., Liu, J. (2006). Content-Based Human Motion Retrieval with Automatic Transition. In: Nishita, T., Peng, Q., Seidel, HP. (eds) Advances in Computer Graphics. CGI 2006. Lecture Notes in Computer Science, vol 4035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784203_31
Download citation
DOI: https://doi.org/10.1007/11784203_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35638-7
Online ISBN: 978-3-540-35639-4
eBook Packages: Computer ScienceComputer Science (R0)