文章基本信息

标题：Salient Region Detection based on Global Contrast and Object-Biased Gaussian Refinement
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作者：Zhang, Xing ; Zhang, Xiaolin
期刊名称：Journal of Multimedia
印刷版ISSN：1796-2048
出版年度：2014
卷号：9
期号：7
页码：941-947
DOI：10.4304/jmm.9.7.941-947
语种：English
出版社：Academy Publisher
摘要：In this study, we address the problem of salient region detection. Recently, salient region detection methods with histogram-based contrast and region-based contrast have given promising results. Center bias is a hypothetical characteristic in human vision system which is applied in many existing salient region detection methods. In this paper, we propose an object-biased Gaussian model to refine the histogram-based contrast method and region contrast method. The proposed algorithm is simple, efficient, and produces full-resolution, high-quality saliency maps. We extensively evaluated our algorithm using traditional salient object detection benchmark, as well as a more challenging co-saliency object detection benchmark. Experimental results demonstrate that the proposed algorithm outperforms the original global contrast methods and other existing salient object detection methods.
关键词：Visual Attention;Color Contrast;Saliency;Gaussian Refinement