基于优化的RGBD图像显著性检测

Zhengchao Lei, Weiyan Chai, Sanyuan Zhao, Hongmei Song, Fengxia Li
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引用次数: 3

摘要

图像显著性检测因其在众多多媒体应用中的应用而备受关注。本文提出了一种基于优化的RGBD图像显著性检测方法。对于RGBD图像,我们的方法利用深度通道来增强背景和前景区域的识别。首先利用非线性变换和突出目标区域生成新的深度图像;然后,引入显著性优化框架,对深度线索和其他低层次线索进行整合,得到最终的显著性图。实验结果表明,该方法对RGBD图像的显著性检测有较好的效果。
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Saliency detection for RGBD image using optimization
Saliency detection in images attracts much research attention for its usage in numerous multimedia applications. In this paper, we propose a saliency detection method based on optimization for RGBD images. With RGBD images, our method utilizes the depth channel to enhance the identification of background and foreground regions. We firstly generate new depth image by using non-linear transformation and outstand object region. Then, we introduce saliency optimization framework to integrate the depth cue and other low-level cues to obtain the final saliency map. The experimental results demonstrate that our method performs better in saliency detection for RGBD Images.
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