Saliency detection based on superpixels clustering and stereo disparity

被引:0
|
作者
Shan-shan Gao
Jing Chi
Li Li
Ji-biao Zou
Cai-ming Zhang
机构
[1] Shandong University of Finance and Economics,School of Computer Science and Technology
[2] Shandong University,School of Computer Science and Technology
[3] Shandong Provincial Key Laboratory of Digital Media Technology,undefined
来源
Applied Mathematics-A Journal of Chinese Universities | 2016年 / 31卷
关键词
Saliency detection; superpixels; stereo disparity; spatial coherence;
D O I
暂无
中图分类号
学科分类号
摘要
Reliable saliency detection can be used to quickly and effectively locate objects in images. In this paper, a novel algorithm for saliency detection based on superpixels clustering and stereo disparity (SDC) is proposed. Firstly, we use an improved superpixels clustering method to decompose the given image. Then, the disparity of each superpixel is computed by a modified stereo correspondence algorithm. Finally, a new measure which combines stereo disparity with color contrast and spatial coherence is defined to evaluate the saliency of each superpixel. From the experiments we can see that regions with high disparity can get higher saliency value, and the saliency maps have the same resolution with the source images, objects in the map have clear boundaries. Due to the use of superpixel and stereo disparity information, the proposed method is computationally efficient and outperforms some state-of-the-art colorbased saliency detection methods.
引用
收藏
页码:68 / 80
页数:12
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