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A two-stage approach to saliency detection in images

Researches in psychology, perception and related fields show that there may be a two-stage process involved in human vision. In this paper, we propose an approach by following a two-stage framework for saliency detection. In the first stage, we extend an existing spectrum residual model for better locating visual pop-outs, while in the second stage we make use of coherence based propagation for further refinement of the results from the first step. For evaluation of the proposed approach, 300 images with diverse contents were manually and accurately labeled. Experiments show that our approach achieves much better performance than that from the existing state-of-art.