Saliency detection from joint embedding of spatial and color cues

Visual saliency detection provides an important methodology for many computer vision applications. In this paper, we propose a novel method to detect salient regions from an image. To detect pixel-level saliency, this method uses joint embedding of spatial and color cues, i.e., spatial constraint based saliency, color double-opponent saliency, and similarity distribution based saliency. Finally, a multi-layer structure is adopted to merge the three terms into a saliency map. In order to make the saliency map consistent, we perform a region-based saliency detection by incorporating a multi-scale segmentation technique. The proposed method was evaluated on the MSRA benchmark images. Experimental results show that our method outperforms the state-of-the-art methods on visual saliency detection by achieving both higher precision and better recall.