Name
Abstract | ||
|---|---|---|
As a measure of regional importance in agreement with human perception of 3D shape, mesh saliency should be based on local geometric information within a mesh but more than that. Recent research has shown that global consideration has a significant role in mesh saliency. This paper proposes a local-to-global framework for computing mesh saliency where we offer novel solutions to solve three inherent problems: (1) an algorithm based on statistic Laplacian which does not only compute local saliency, but also facilitates the later computation of global saliency; (2) a local-to-global method based on pooling and global distinctness to compute global saliency; (3) a framework to integrate local and global saliency. Experiments demonstrate that our approach can effectively detect salient features consistent with human perceptual interest. We also provide comparisons to existing state-of-the-art methods for mesh saliency and show improved results produced by our method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s00371-016-1334-9 | The Visual Computer |
Keywords | DocType | Volume |
Mesh saliency, Laplacian, Global distinctness | Journal | 34 |
Issue | ISSN | Citations |
3 | 1432-2315 | 4 |
PageRank | References | Authors |
0.40 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ran Song | 1 | 53 | 11.70 |
| Yonghuai Liu | 2 | 675 | 61.65 |
| Ralph R. Martin | 3 | 3279 | 240.42 |
| Karina Rodriguez-Echavarria | 4 | 50 | 5.81 |