Name
Abstract | ||
|---|---|---|
In this paper, we deal with the problem of synthesizing novel motions of standing-up martial arts such as Kickboxing, Karate, and Taekwondo performed by a pair of human-like characters while reflecting their interactions. Adopting an example-based paradigm, we address three non-trivial issues embedded in this problem: motion modeling, interaction modeling, and motion synthesis. For the first issue, we present a semi-automatic motion labeling scheme based on force-based motion segmentation and learning-based action classification. We also construct a pair of motion transition graphs each of which represents an individual motion stream. For the second issue, we propose a scheme for capturing the interactions between two players. A dynamic Bayesian network is adopted to build a motion transition model on top of the coupled motion transition graph that is constructed from an example motion stream. For the last issue, we provide a scheme for synthesizing a novel sequence of coupled motions, guided by the motion transition model. Although the focus of the present work is on martial arts, we believe that the framework of the proposed approach can be conveyed to other two-player motions as well. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/TVCG.2008.22 | IEEE Trans. Vis. Comput. Graph. |
Keywords | Field | DocType |
motion synthesis,last issue,semi-automatic motion,individual motion stream,motion transition graph,motion transition model,example motion stream,synthesizing novel motion,force-based motion segmentation,motion modeling,two-character motion analysis,dynamic bayesian network,image classification,graph theory,animation,bayesian methods,martial art,image segmentation,layout,learning artificial intelligence,leg,network synthesis,arm,art,computer vision | Graph theory,Computer vision,Computer science,Segmentation,Character animation,Image segmentation,Theoretical computer science,Artificial intelligence,Animation,Motion analysis,Contextual image classification,Dynamic Bayesian network | Journal |
Volume | Issue | ISSN |
14 | 3 | 1077-2626 |
Citations | PageRank | References |
23 | 0.84 | 39 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taesoo Kwon | 1 | 800 | 56.37 |
| Young-Sang Cho | 2 | 56 | 2.32 |
| Sang Il Park | 3 | 496 | 26.33 |
| Sung Yong Shin | 4 | 1904 | 168.33 |