Name
Abstract | ||
|---|---|---|
The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. This paper presents a simple method for the visual saliency detection.Our model is independent of features, categories, or other forms of prior knowledge of the objects. By analyzing the log-spectrum of an input image, we extract the spectral residual of an image in spectral domain, and propose a fast method to construct the corresponding saliency map in spatial domain.We test this model on both natural pictures and artificial images such as psychological patterns. The result indicate fast and robust saliency detection of our method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CVPR.2007.383267 | 2007 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-8 |
Keywords | Field | DocType |
spectrum,image analysis,object recognition,visual system,computational modeling,redundancy,feature extraction,machine vision,statistical distributions,human visual system | Object detection,Computer vision,Residual,Machine vision,Kadir–Brady saliency detector,Pattern recognition,Human visual system model,Computer science,Salience (neuroscience),Feature extraction,Artificial intelligence,Cognitive neuroscience of visual object recognition | Conference |
Volume | Issue | ISSN |
2007 | 1 | 1063-6919 |
Citations | PageRank | References |
1273 | 46.74 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaodi Hou | 1 | 2069 | 72.53 |
| Liqing Zhang | 2 | 2713 | 181.40 |