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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Goferman, Stas Zelnik-Manor, Lihi Tal, Ayellet |
| Copyright Year | 1979 |
| Abstract | We propose a new type of saliency—context-aware saliency—which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting, we demonstrate that using our saliency prevents distortions in the important regions. In summarization, we show that our saliency helps to produce compact, appealing, and informative summaries. |
| Sponsorship | IEEE Computer Society |
| Page Count | 12 |
| File Size | 2778051 |
| Starting Page | 1915 |
| Ending Page | 1926 |
| File Format | |
| ISSN | 01628828 |
| Volume Number | 34 |
| Issue Number | 10 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Context awareness Visualization Object recognition Estimation Image color analysis Human factors context aware. Image saliency visual saliency |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Artificial Intelligence Computational Theory and Mathematics Computer Vision and Pattern Recognition Software |
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