Abstract
Saliency detection is one of the most challenging problems in the fields of image analysis and computer vision. Many approaches propose different architectures based on the psychological and biological properties of the human visual attention system. However, there is not still an abstract framework, which summarized the existing methods. In this paper, we offered a general framework for saliency models, which consists of five main steps: pre-processing, feature extraction, saliency map generation, saliency map combination, and post-processing. Also, we study different saliency models containing each level and compare their performance together. This framework helps researchers to have a comprehensive view of studying new methods.
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