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Perceptually Guided Synthesis and Compression of Motion Capture Data Open Access


Other title
Data Compression
Perceptual Quality
Motion Capture
Type of item
Degree grantor
University of Alberta
Author or creator
Firouzmanesh, Amirhossein
Supervisor and department
Cheng, Irene (Computing Science)
Basu, Anup (Computing Science)
Examining committee member and department
Boulanger, Pierre (Computing Science)
Dufaux, Frédéric (Telecom ParisTech)
Salavatipour, Mohammad R. (Computing Science)
Department of Computing Science

Date accepted
Graduation date
Doctor of Philosophy
Degree level
Using motion capture data is an efficient way to generate and transmit 3D character animation. We explore the possibility of incorporating human perceptual factors in compression and synthesis of motion capture data in order to achieve a higher performance in different aspects including reducing the bandwidth requirement, decreasing processing time and transmission delay in different scenarios. First we show that by incorporating perceptual factors in wavelet-based compression, the processing time could be significantly reduced without noticeable degradation in the reconstruction quality. Experimental analysis shows that the proposed algorithm is much faster than comparable approaches using wavelets, thereby making our approach feasible for motion capture transmission, and real-time synthesis on mobile devices, where processing power and memory capacity are limited. We also propose a compression method based on using motion primitives. Using incremental encoding plus a database of motion primitives for each key point, our method achieves a higher or competitive compression rate with less online overhead. Trade-off between visual quality and bandwidth usage can be tuned by varying a single threshold value. A user study was performed to measure the sensitivity of human subjects to reconstruction errors in key rotation angles. While achieving real-time performance, our technique outperforms other methods in our experiments by achieving a compression ratio exceeding 50:1 on regular sequences without noticeable degradation in rendered qualities. Finally we propose a high efficiency, fast, scalable method for compressing motion capture clips taking advantage of a 1-D variation of the SPIHT algorithm. SPIHT provides near-optimal reconstruction error using the allocated bits. A 1-D variation of the original SPIHT is proposed that works with individual channels of motion capture data. Instead of time-consuming optimization process we combine 1-D SPIHT with a bit rate allocation mechanism based on perceptual factors to distribute the available bandwidth between the channels of data based on their importance in perceptual reconstruction quality of the motion. Our studies show that the proposed method is capable of compressing data at a rate of 40:1 to 60:1 with close to perfect reconstruction quality, which is generally better than the current methods in the literature.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
A. Firouzmanesh, I. Cheng, A. Basu,“Perceptually guided fast compression of 3-d motion capture data,” IEEE Transactions on Multimedia, vol. 13,issue 4, 829-834A. Firouzmanesh, M. Lindgren, T. Drummond, I. Cheng, A. Basu,“ Efficient compression of rhythmic motion using spatial segmentation and temporal blending,” Proceeding of IEEE Multimedia and Expo Workshops (ICMEW), 2013A. Firouzmanesh, I. Cheng, A. Basu,“ Perceptually Motivated Real-Time Compression of Motion Data Enhanced by Incremental Encoding and Parameter Tuning,” Proceedings of Eurographics 2013-Short Papers

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