Combine multi-level features including local contrast, global contrast, and background priors which measure the visual saliency in pixel-level, region-level, and object-level.

We use the low level visual cues based on the convex hull to separate salient object from the background. The background priors of object are computed from the background templates using PCA.

In order to suppress background noise, local and global contrasts are refined by object center priors which are computed with the Gaussian model based on background priors.