Name
Abstract | ||
|---|---|---|
Multiresolution motion analysis has gained great research interest as a unified framework to facilitate a va- riety of motion editing tasks. In this framework, motion data are represented as a collection of coefficients that form a coarse-to-fine hierarchy. The coefficients at the coarsest level describe the global pattern of a motion signal, while those at fine levels provide different details at successively finer resolutions. Due to the inherent non-linearity of the orientation space, it is challenging to generalize multiresolution representations for motion data that contain orientations as well as positions. Our goal is to develop a multiresolution analysis method which guarantees coordinate-invariancewithout any singularity. To do so, we employ two novel ideas, that is, hierarchical displacement mapping and motion filtering. The notion of hierarchical displacement mapping provides an elegant formulation to describe positions and orientations in a coherent manner. With the mo- tion filters, we are able to separate motion details level-by-level to build a multiresolution representation in a coordinate-invariant way. Our representation facilitates multiresolution motion editing through level-wise coefficient manipulation to uniformly address issues raised by motion modification, blending, and stitching. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1006/gmod.2001.0548 | Graphical Models |
Keywords | Field | DocType |
motion editing,motion signal processing,coordinate-invariant approach,multiresolution analysis,hierarchical techniques,motion analysis,coordinate- invariance.,coordinate-invariance,motion filtering | Structure from motion,Computer vision,Image stitching,Motion field,Filter (signal processing),Multiresolution analysis,Displacement mapping,Artificial intelligence,Motion estimation,Motion analysis,Mathematics | Journal |
Volume | Issue | ISSN |
63 | 2 | Graphical Models |
Citations | PageRank | References |
25 | 1.62 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jehee Lee | 1 | 1912 | 118.33 |
| Sung Yong Shin | 2 | 1904 | 168.33 |