Name
Abstract | ||
|---|---|---|
With the rapid growing advancement of animation technologies, 3D animated meshes are becoming one of the major data in the industry such as virtual reality. However, treating the animated mesh data efficiently remains a challenging task due to its large scale and limited feature descriptors. In this paper, we present an evolutionary signature for animated meshes based on tempo-spatial segmentation. In specific, we first conduct temporal segmentation to a given animated meshes with sub-motions, then apply spatial segmentation within each temporal segment, and intersect spatial segmentation result for over segmentation. Thirdly, we represent the segmentation results into graphs. Finally, we devise an edge evolution matrix based on the dynamic behaviour of each edge for the evolutionary signature of the input animated mesh. Our experimental results on similarity measurement by using the proposed signature reflect the effectiveness of our method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/PacificVis.2018.00038 | 2018 IEEE Pacific Visualization Symposium (PacificVis) |
Keywords | Field | DocType |
animated mesh,evolutionary signature,segmentation | Computer vision,Polygon mesh,Virtual reality,Computer science,Segmentation,Feature extraction,Solid modeling,Animation,Computer facial animation,Artificial intelligence,The Intersect | Conference |
ISSN | ISBN | Citations |
2165-8765 | 978-1-5386-1425-9 | 0 |
PageRank | References | Authors |
0.34 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoliang Luo | 1 | 14 | 2.88 |
| Hao-Peng Lei | 2 | 4 | 2.41 |
| Yugen Yi | 3 | 92 | 15.25 |
| Yuhua Li | 4 | 19 | 8.06 |
| Chuahua Xian | 5 | 0 | 0.34 |