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.
Goferman et al. REF propose context-aware saliency, which detects the important parts of the scene rather than the traditional salient object.
Context-aware saliency detection
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Computer Science Medicine