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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaodi Hou Liqing Zhang |
| Copyright Year | 2007 |
| Description | Author affiliation: Shanghai Jiao Tong Univ., Shanghai (Xiaodi Hou; Liqing Zhang) |
| 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. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 1693978 |
| Page Count | 8 |
| File Format | |
| ISBN | 1424411793 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2007.383267 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-06-17 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Object detection Computational modeling Humans Visual system Image analysis Object recognition Machine vision Redundancy Image coding Statistical distributions |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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