Hierarchical Image Saliency Detection on Extended CSSD

Chinese University of Hong Kong · Lenovo (China)

PubMed
Indexed incrossrefpubmed

Abstract

Complex structures commonly exist in natural images. When an image contains small-scale high-contrast patterns either in the background or foreground, saliency detection could be adversely affected, resulting erroneous and non-uniform saliency assignment. The issue forms a fundamental challenge for prior methods. We tackle it from a scale point of view and propose a multi-layer approach to analyze saliency cues. Different from varying patch sizes or downsizing images, we measure region-based scales. The final saliency values are inferred optimally combining all the saliency cues in different scales using hierarchical inference. Through our inference model, single-scale information is selected to obtain a…

Citation impact

587
total citations
FWCI
26.58
Percentile
100%
References
53
Citations per year

Authors

4

Topics & keywords

Keywords
  • Artificial intelligence
  • Computer science
  • Inference
  • Pattern recognition (psychology)
  • Image (mathematics)
  • Contrast (vision)
  • Scale (ratio)
  • Construct (python library)
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