caa a22 4500 605540357 CHVBK 20210128100911.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00371-014-1034-2 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1034-2 Correlation-optimized time warping for motion [Elektronische Daten] [S. Etemad, Ali Arya] Retrieval and comparative editing/modeling of motion data require temporal alignment. In other words, for such processes to perform accurately, critical features of motion sequences need to occur simultaneously. In this paper, we propose correlation-optimized time warping (CoTW) for aligning motion data. CoTW utilizes a correlation-based objective function for characterizing alignment. The method solves an optimization problem to determine the optimum warping degree for different segments of the sequence. Using segment-wise interpolated warping, smooth motion trajectories are achieved that can be readily used for animation. Our method allows for manual tuning of the parameters, resulting in high customizability with respect to the number of actions in a single sequence as well as spatial regions of interest within the character model. Moreover, measures are taken to reduce distortion caused by over-warping. The framework also allows for automatic selection of an optimum reference when multiple sequences are available. Experimental results demonstrate the very accurate performance of CoTW compared to other techniques such as dynamic time warping, derivative dynamic time warping and canonical time warping. The mentioned customization capabilities are also illustrated. Springer-Verlag Berlin Heidelberg, 2014 Motion analysis nationallicence Time warping nationallicence Temporal alignment nationallicence Correlation nationallicence Optimization nationallicence Etemad S. School of Information Technology, Carleton University, Ottawa, ON, Canada aut Arya Ali School of Information Technology, Carleton University, Ottawa, ON, Canada aut The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1569-1586 0178-2789 31:12<1569 2015 31 371 https://doi.org/10.1007/s00371-014-1034-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1034-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Etemad S. School of Information Technology, Carleton University, Ottawa, ON, Canada aut NATIONALLICENCE 700 1- Arya Ali School of Information Technology, Carleton University, Ottawa, ON, Canada aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1569-1586 0178-2789 31:12<1569 2015 31 371