Title
Matching and blending human motions temporal scaleable dynamic programming
Abstract
This paper presents a method for matching the frames of the human motions acquired by a motion capture system, and then creating blended (interpolated) motions according to the matching result. This matching method is basically a variation of a dynamic programming (DP) matching but we enhanced it to enable it to detect the timescale parameters. This scaleable dynamic programming (scaleable-DP) can match and evaluate the same class of motions such as walking, running, stepping and their timescale parameters. This approach is adaptable for differences in individuals, such as body sizes and timing of the stop-frames. On the blending pipeline, we first generate the keyframes according to the matching result. The keyframes are generated by considering the spatial and temporal difference of individual motions. After that, transition motions are synthesized between the keyframes. We experimented with our approach by using 15 gait motions and 5 dance motions. The results of these demonstrations show the validity of the proposed algorithm.
Year
DOI
Venue
2004
10.1109/IROS.2004.1389366
IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference
Keywords
Field
DocType
dynamic programming,image matching,image motion analysis,interpolation,blending pipeline,frame matching,human motion,interpolated motion,motion capture system,scaleable dynamic programming
Dynamic programming,Computer vision,Motion capture,Temporal difference learning,Image matching,Computer science,Interpolation,Artificial intelligence
Conference
Volume
ISBN
Citations 
1
0-7803-8463-6
6
PageRank 
References 
Authors
0.50
7
3
Name
Order
Citations
PageRank
Atsushi Nakazawa150734.25
Shinichiro Nakaoka246132.58
Katsushi Ikeuchi34651881.49