Name
Abstract | ||
|---|---|---|
Motion editing methods have been widely used to create realistic human animation, which is vital to maintain footplant constrains during motion editing process. In this paper, we present a simple but efficient way for footplant constraints detection. Existing methods for automatic footplant detection are all software-based which are sensitive to motion data noises. We improve this work by hardware instead. We equip the actor with a simple pressure trigger circuit under his shoes. Whenever the toes or heels of the actor touch the ground, the circuit will be switched on and this information will be captured by motion capture system. Combining this additional information with the ordinary captured motion data, we can identify footplant constraints effectively. Such additional information will then be saved into the output motion capture file and can be used conveniently by the user. The new framework we developed can provide more precise detection results than previous software-based methods. Moreover, by pre-computing the footplant constraints, the time for footplant constraints detection in previous software-based methods can be saved. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/CGIV.2005.23 | CGIV |
Keywords | Field | DocType |
motion data noise,footplant constraint,previous software-based method,motion data,motion capture system,computer animation,realistic images,realistic human animation,motion estimation,motion editing method,automatic foot-plant constraints detection,footplant constraints detection,additional information,motion editing process,software-based method,output motion capture file,automatic foot-plant constraint detection shoes,automatic footplant detection,animation,computer graphics,motion capture,hardware | Computer vision,Motion capture,Motion detection,Computer science,Software,Animation,Artificial intelligence,Motion estimation,Motion editing,Computer animation,Computer graphics | Conference |
ISBN | Citations | PageRank |
0-7695-2392-7 | 1 | 0.36 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Gao | 1 | 2 | 1.11 |
| Lizhuang Ma | 2 | 498 | 100.70 |
| Xiaomao Wu | 3 | 52 | 5.05 |
| Zhihua Chen | 4 | 23 | 4.18 |