Name
Abstract | ||
|---|---|---|
In this paper, visual attention spreading is formulated as a nonlocal diffusion equation. Different from other diffusion-based methods, a nonlocal diffusion tensor is introduced to consider both the diffusion strength and the diffusion direction. With the help of diffusion tensor, along with the principle direction, the diffusion has been suppressed to preserve the dissimilarity between the foreground and background, while in other directions, the diffusion has been boosted to combine the similar regions and highlight the salient object as a whole. Through a two-stages diffusion, the final saliency maps are obtained. Extensive quantitative or visual comparisons are performed on three widely used benchmark datasets, i.e. MSRA-ASD, MSRA-B and PASCAL-1500 datasets. Experimental results demonstrate the superior performance of our method. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1142/S0218001415550137 | International Journal of Pattern Recognition and Artificial Intelligence |
Keywords | Field | DocType |
REGION DETECTION,VISUAL-ATTENTION,MODEL,STATISTICS,FRAMEWORK | Anisotropic diffusion,Diffusion MRI,Salient object detection,Salience (neuroscience),Salient objects,Artificial intelligence,Diffusion map,Computer vision,Pattern recognition,Visual attention,Mathematics,Diffusion equation,Machine learning | Journal |
Volume | Issue | ISSN |
29 | 7 | 0218-0014 |
Citations | PageRank | References |
3 | 0.37 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiujun Zhang | 1 | 21 | 2.39 |
| Chen Xu | 2 | 269 | 29.36 |
| Xiaoli Sun | 3 | 26 | 5.49 |
| George Baciu | 4 | 409 | 56.17 |