Abstract
Motion capturing has become an important tool in fields such as sports sciences, biometrics, and particularly in computer animation, where large collections of motion material are accumulated in the production process. In order to fully exploit motion databases for reuse and for the synthesis of new motions, one needs efficient retrieval and browsing methods to identify similar motions. So far, only ad-hoc methods for content-based motion retrieval have been proposed, which lack efficiency and rely on quantitative, numerical similarity measures, making it difficult to identify logically related motions. We propose an efficient motion retrieval system based on the query-by-example paradigm, which employs qualitative, geometric similarity measures. This allows for intuitive and interactive browsing in a purely content-based fashion without relying on textual annotations. We have incorporated this technology in a novel user interface facilitating query formulation as well as visualization and ranking of search results.
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References
CMU, Carnegie-Mellon MoCap Database. Created with funding from NSF EIA- 0196217 (2003), http://mocap.cs.cmu.edu
Forbes, K., Fiume, E.: An efficient search algorithm for motion data using weighted PCA. In: SCA 2005: Proc. 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 67–76. ACM Press, New York (2005)
Keogh, E.J., Palpanas, T., Zordan, V.B., Gunopulos, D., Cardle, M.: Indexing large human-motion databases. In: Proc. 30th VLDB Conf., Toronto, pp. 780–791 (2004)
Kovar, L., Gleicher, M.: Automated extraction and parameterization of motions in large data sets. ACM Trans. Graph. 23, 559–568 (2004)
Liu, G., Zhang, J., Wang, W., McMillan, L.: A system for analyzing and indexing human-motion databases. In: SIGMOD 2005: Proc. 2005 ACM SIGMOD Intl. Conf. on Management of Data, pp. 924–926. ACM Press, New York (2005)
Müller, M., Röder, T., Clausen, M.: Efficient content-based retrieval of motion capture data. ACM Trans. Graph. 24, 677–685 (2005)
Vicon, 3D optical motion capture, http://www.vicon.com
Wu, M.-Y., Chao, S., Yang, S., Lin, H.: Content-based retrieval for human motion data. In: 16th IPPR Conf. on Computer Vision, Graphics and Image Processing, pp. 605–612 (2003)
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© 2006 Springer-Verlag Berlin Heidelberg
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Demuth, B., Röder, T., Müller, M., Eberhardt, B. (2006). An Information Retrieval System for Motion Capture Data. In: Lalmas, M., MacFarlane, A., Rüger, S., Tombros, A., Tsikrika, T., Yavlinsky, A. (eds) Advances in Information Retrieval. ECIR 2006. Lecture Notes in Computer Science, vol 3936. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11735106_33
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DOI: https://doi.org/10.1007/11735106_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33347-0
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