Abstract
This paper proposes a keyframe extraction method based on a novel layered curve simplification algorithm for motion capture data. Bone angles are employed as motion features and keyframe candidates can be selected based on them. After that, the layered curve simplification algorithm will be used to refine those candidates and the keyframe collection can be gained. To meet different requirements for compression and level of detail of motion abstraction, adaptive extraction parameters are also applied. The experiments demonstrate that our method can not only compress and summarize the motion capture data efficiently, but also keep the consistency of keyframe collection between similar human motion sequences, which is of great benefit to further motion data retrieval or editing.
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References
Terra, S.C.L., Metoyer, R.A.: Performance Timing for Keyframe Animation. In: Proceedings of Eurographics/ACM SIGGRAPH Symposium on Computer Animation, pp. 253–258 (2004)
Whitaker, H., Halas, J.: Timing for Animation. Focal Press, Burlington (1981)
Parent, R.: Computer Animation: Algorithms and Techniques. Morgan Kaufmann, San Francisco (2001)
Liu, F., et al.: 3d Motion Retrieval with Motion Index Tree[J]. Computer Vision and Image Understanding 92(2-3), 265–284 (2003)
Junxing, S., Shouqian, S., Yunhe, P.: Key-Frame Extraction from Motion Capture Data. Journal of Computer-aided Design & Computer Graphics 16(5), 719–723 (2004)
Lim, I.S., Thalmann, D.: Key-Posture Extraction Out of Human Motion Data by Curve Simplification[C]. In: Proc. EMBC2001, 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1167–1169 (2001)
Pickering, M.J., Ruger, S.: Evaluation of key frame-based retrieval techniques for video. Comput. Vis. Image Understand 92(2), 217–235 (2003)
Zhuang, Y., Rui, Y., Huang, T.S.: Adaptive Key Frame Extraction Using Unsupervised Clustering[A]. In: IEEE ICIP 1998, Chicago, USA (October 1998)
Zhuang, Y., Pan, Y., Wu, F.: Web-based Multimedia Information Analysis and Retrieval. Tsinghua University Press (2002)
Barbic, J., Safonova, A., Pan, J.-Y., Faloutsos, C., Hodgins, J.K., Pollard, N.S.: Segmenting Motion Capture Data into Distinct Behaviors. In: Proceedings of Graphics Interface, pp. 185–194 (2004)
Brand, M.E., Kettnaker, V.: Discovery and segmentation of activities in video. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI) 22(8), 844–851 (2000)
Park, M.J., Shin, S.Y.: Example-based motion cloning. Comput. Animat. Virtual Worlds 15(3-4), 245–257 (2004)
Huang, K.-S., Chang, C.-F., Hsu, Y.-Y., Yang, S.-N.: Key Probe: a technique for animation keyframe extraction. The Visual Computer 21(8-10), 532–541 (2005)
Lee, J., Chai, J., Reitsma, P.S.A., Hodgins, J.K., Pollard, N.S.: Interactive Control of Avatars Animated with Human Motion Data[A]. In: Proceedings SIGGRAPH 2002[C], San Antonio, Texas, pp. 491–500 (2002)
Chui, C.Y., Chao, S.P., Wu, M.Y., Yang, S.N., Lin, H.C.: Content-based Retrieval for Human Motion Data[J]. Journal of Visual Communication and Image Representation 16(3), 446–466 (2004)
Mueller, M., Roeder, T., Clausen, M.: Efficient Content-Based Retrieval of Motion Capture Data[A]. In: Proceedings of ACM SIGGRAPH 2005[C], vol. 24(3), pp. 677–685 (2005)
Rosin, P.L.: Techniques for Assessing Polygonal Approximations of Curve[J]. IEEE Transactions on Pattern Recognition and Machine Intelligence 19(6), 659–666 (1997)
Fritsch, F.N., Carlson, R.E.: Monotone Piecewise Cubic Interpolation. SIAM J. Numerical Analysis 17, 238–246 (1980)
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Xiao, J., Zhuang, Y., Yang, T., Wu, F. (2006). An Efficient Keyframe Extraction from Motion Capture Data. 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_44
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DOI: https://doi.org/10.1007/11784203_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35638-7
Online ISBN: 978-3-540-35639-4
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