A Brief Survey of Low-Level Saliency Detection
| Autor: | Shuilong Dong, Xiaobin Zhu, Haisheng Li, Lei Wang |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Image segmentation computer.software_genre Field (computer science) Electronic mail Object detection Visualization Object-class detection 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining Set (psychology) computer |
| Zdroj: | 2016 International Conference on Information System and Artificial Intelligence (ISAI). |
| DOI: | 10.1109/isai.2016.0130 |
| Popis: | Saliency detection is a challenging problem and one of the most active research topics in the field of computer vision. Application scenarios of saliency detection range from surveillance to retrieval, from industrial safety to sports analysis. Given the broad set of techniques used in saliency detection and the fast progress in this area, in this paper we briefly survey the corresponding literature on the low-level methods. In our thoroughly experimental comparison, the state-of-the-art research on saliency detection is analyzed and presented in detail. The advantages and the drawbacks of the methods are critically discussed, providing a comprehensive coverage of key aspects of low-level saliency detection. Finally, the development tendency of saliency detection is predicted. |
| Databáze: | OpenAIRE |
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