Name
Abstract | ||
|---|---|---|
In this paper, we present an online algorithm to normalize all motion data in database with a common skeleton length. Our algorithm is very simple and efficient. The input motion stream is processed sequentially while the computation for a single frame at each step requires only the results from the previous step over a neighborhood of nearby backward frames. In contrast to previous motion retargeting approaches, we simplify the constraint condition of retargeting problem, which leads to the simpler solutions. Moreover, we improve Shin et al.'s algorithm [10], which is adopted by a widely used Kovar's footskate cleanup algorithm [6] through adding one case missed by it. |
Year | DOI | Venue |
|---|---|---|
2005 | null | Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST |
Keywords | Field | DocType |
retargeting problem,simpler solution,constraint condition,motion data,common skeleton length,previous step,footskate cleanup algorithm,online algorithm,previous motion,input motion stream,motion normalization,motion capture | Online algorithm,Motion capture,Computer vision,Motion field,Quarter-pixel motion,Normalization (statistics),Simulation,Computer science,Retargeting,Artificial intelligence,Motion estimation,Computation | Conference |
Volume | Issue | ISSN |
2006 | null | null |
ISBN | Citations | PageRank |
1-59593-098-1 | 1 | 0.41 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Gao | 1 | 2 | 1.11 |
| Lizhuang Ma | 2 | 498 | 100.70 |
| Zhihua Chen | 3 | 23 | 4.18 |
| Xiaomao Wu | 4 | 52 | 5.05 |