Issue No. 04 - April (2011 vol. 17)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.87
Jen-Yu Peng , National Chiao Tung University, Hsinchu City
I-Chen Lin , National Chiao Tung University, Hsinchu City
Ming-Han Tsai , National Chiao Tung University, Hsinchu City
Chao-Chih Lin , National Chiao Tung University, Hsinchu City
In this paper, we present a representation method for motion capture data by exploiting the nearly repeated characteristics and spatiotemporal coherence in human motion. We extract similar motion clips of variable lengths or speeds across the database. Since the coding costs between these matched clips are small, we propose the repeated motion analysis to extract the referred and repeated clip pairs with maximum compression gains. For further utilization of motion coherence, we approximate the subspace-projected clip motions or residuals by interpolated functions with range-aware adaptive quantization. Our experiments demonstrate that the proposed feature-aware method is of high computational efficiency. Furthermore, it also provides substantial compression gains with comparable reconstruction and perceptual errors.
Three-dimensional graphics and realism-animation, Compression (coding)-approximate methods.
Jen-Yu Peng, I-Chen Lin, Ming-Han Tsai, Chao-Chih Lin, "Adaptive Motion Data Representation with Repeated Motion Analysis", IEEE Transactions on Visualization & Computer Graphics, vol. 17, no. , pp. 527-538, April 2011, doi:10.1109/TVCG.2010.87