Motion Data Denoising Based on the Quaternion Lifting Scheme Multiresolution Transform

• Autorzy: Szczesna, A. , Slupik, J. , Janiak, M.
• Języki publikacji: EN

Abstrakty

EN

We discuss human body motion denoising with use of the transform based on second generation wavelet. To build such a transform, we use the quaternion lifting scheme. The main focus is placed on representing body parts orientation changes over time with quaternions as a technique both compact and more efficient than the representation of the Euler angles of rotation. Our denoising method is based on a soft threshold algorithm but is directly to the quaternion motion data in the resulting multiresolution representation.

Słowa kluczowe

EN

quaternions; multiresolution analysis; wavelet transform; lifting scheme; motion data denoising

• Czasopismo: Machine Graphics and Vision
• Rocznik: 2011
• Tom: Vol. 20, No. 3
• Strony: 237-249
• Opis fizyczny: Bibliogr. 19 poz., wykr.

Twórcy

autor

Szczesna, A.

• The Silesian University of Technology, Institute of Informatics, Gliwice, Poland

autor

Slupik, J.

• The Silesian University of Technology, Institute of Mathematics, Gliwice, Poland

autor

Janiak, M.

• The Silesian University of Technology, Institute of Informatics, Gliwice, Poland

Bibliografia

• [1] Bruderlin A., Williams L.: Motion signal processing. Proceeding SIGGRAPH of the 22nd annual conference on Computer graphics and interactive techniques, 1995.
• [2] Sweldens W.: The Lifting Scheme: A new philosophy in biorthogonal wavelet constructions. Wavelet Applications in Signal and Image Processing III, 1995.
• [3] Lee J., Shin S. Y.: Motion fairing. Proceedings of Computer Animation 96, 136-143, 1996.
• [4] Stollnitz E. J., DeRose T., Salesin D. H.: Wavelets for Computer Graphics: Theory and Applications. Morgan Kaufmann, 1996.
• [5] Fioretti S.: Signal processing in movement analysis (a state-space approach). Human Movement Science, 15 (3), 389-410, 1996.
• [6] Sweldens W.: The lifting scheme: A construction of second generation wavelets. SIAM J. Math. Anal., 1997.
• [7] Fang Y., Hsieh C. C., Kim M.J ., Chang J. J., Woo T. C.: Real time motion fairing with unit quaternions. Computer-Aided Design, 30 (3), 191-198, 1998.
• [8] Daubechies I., Guskov I., Schröder P., Sweldens W.: Wavelets on Irregular Point Sets. Royal Society, 1999.
• [9] Guskov I., Sweldens W., Schröder P.: Multiresolution Signal Processing for Meshes. Computer Graphics Proceedings, 1999.
• [10] Lee J., Shin S. Y.: A coordinate-invariant approach to multiresolution motion analysis. Graphical Models and Image Processing, 63 (2), 87-105, 2001.
• [11] Hsieh Ch.-Ch.: B-spline wavelet-based motion smoothing. Computers and Industrial Engineering, 2001.
• [12] Shin H. J., Lee J., Gleicher M., Shin S. J.: Computer puppetry: an importance-based approach. ACM Transactions on Graphics, 20 (2), 67-94, 2001.
• [13] Lee J., Shin S. Y.: General construction of timedomain filters for orientation data. IEEE Transactions on Visualization and Computer Graphics, 8 (2), 119-128, 2002.
• [14] Hsieh Ch.-Ch.: Motion Smoothing Using Wavelets. Journal of Intelligent and Robotic Systems 35, 57169, 2002.
• [15] Tak S., Ko H.-S.: A physically-based motion retargeting filter. ACM Transactions on Graphics, 24 (1), 98-117, 2005.
• [16] Jansen M., Oonincx P.: Second Generation Wavelets and Applications. Springer, 2005.
• [17] Beaudoin P., Poulin P., Panne M.: Adapting wavelet compression to human motion capture clips. GI ’07 Proceedings of Graphics Interface, 2007.
• [18] Szczesna A.: The Multiresolution Analysis of Triangle Surface Meshes with Lifting Scheme. In Computer Vision/Computer Graphics Collaboration Techniques, Proceedings of MIRAGE, Gagalowicz A., Philips W. (editors), Springer, LNCS 4418, 274-282, 2007.
• [19] Lou H., Chai J.: Example-based Human Motion Denoising. IEEE Transactions on Visualization and Computer Graphics, 16 (5), 2010.