Physical Sciences and Mathematics Commons^™

Unsupervised Saliency Estimation Based On Robust Hypotheses, Fei Xu, Min Xian, H. D. Cheng, Jianrui Ding, Yingtao Zhang

Computer Science Faculty and Staff Publications

Visual saliency estimation based on optimization models is gaining increasing popularity recently. In this paper, we formulate saliency estimation as a quadratic program (QP) problem based on robust hypotheses. First, we propose an adaptive center-based bias hypothesis to replace the most common image center-based center-bias. It calculates the weighted center by utilizing local contrast which is much more robust when the objects are far away from the image center. Second, we model smoothness term on saliency statistics of each color. It forces the pixels with similar colors to have similar saliency statistics. The proposed smoothness term is more robust than …