Abstract
Visual saliency detection and segmentation are widely used in many applications in image processing and computer vision. However, existing saliency detection methods have not fully taken the spatial information of salient regions into account. Inspired by the basic photographic composition rules, we present a novel saliency detection method, which utilizes the knowledge of photographic composition as priors to improve the saliency detection results. Moreover, an online parameter selection method is proposed when utilizing GrabCut to achieve the saliency segmentation result. We test our method on the 1000 benchmark test images and dataset MSRA. Extensive experimental results show the applicability and effectiveness of our method.
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