Name
Abstract | ||
|---|---|---|
It is well known that visual attention and saliency mechanisms play an important role in human visual perception. This paper proposes a novel bottom-up saliency mechanism through scale space analysis. The research on human perception had shown that our ability to perceive a visual scene with different scales is described with the Contrast-Sensitivity Function (CSF). Motivated by this observation, we model the saliency as weighted average of the multi-scale analysis of the visual scene, where the weights of the middle spatial frequency bands are larger than others, following the CSF. This method is tested on natural images. The experimental results show that this approach is able to quickly extract salient regions which are consistent with human visual perception, both qualitatively and quantitatively. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-24955-6_21 | ICONIP (1) |
Keywords | Field | DocType |
different scale,multi-scale analysis,human visual perception,scale space analysis,scale selectivity,human visual system,visual attention,visual scene,saliency detection,human perception,novel bottom-up saliency mechanism,contrast-sensitivity function,saliency mechanism | Computer vision,Pattern recognition,Human visual perception,Salience (neuroscience),Human visual system model,Computer science,Scale space,Visual attention,Artificial intelligence,Perception,Spatial frequency,Salient | Conference |
Volume | ISSN | Citations |
7062 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fang Fang | 1 | 48 | 5.86 |
| Laiyun Qing | 2 | 337 | 24.66 |
| Jun Miao | 3 | 220 | 22.17 |
| Xilin Chen | 4 | 6291 | 306.27 |
| Wen Gao | 5 | 11374 | 741.77 |