Hierarchical Image Saliency Detection on Extended CSSD
Chinese University of Hong Kong · Lenovo (China)
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
- FWCI
- 26.58
- Percentile
- 100%
- References
- 53
Authors
4Topics & keywords
- Artificial intelligence
- Computer science
- Inference
- Pattern recognition (psychology)
- Image (mathematics)
- Contrast (vision)
- Scale (ratio)
- Construct (python library)