Visual saliency detection with center shift

This paper proposes a novel method for visual saliency detection based on an universal probabilistic model, which measures the saliency by combining low level features and location prior. We view the task of estimating visual saliency as searching the most conspicuous parts in an image and extract the saliency map by computing the dissimilarity between different regions. We simulate the moving of Furthermore, multiscale analysis is adopted for improving the robustness of our model. Experimental results on three public image datasets show that the proposed approach outperforms 18 state-of-the-art methods for both salient object detection and human eye fixation prediction. & 2012 Elsevier B.V. All rights reserved.