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Saliency detection based on global color and space contrast

机译:基于全局颜色和空间对比度的显着性检测

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Saliency detection acts as an important role in many computer vision tasks. We propose a novel bottom-up, object-level saliency detection method based on global color and space contrast. The proposed method not only considers the global color contrast of the image but also takes the space information into account, leading to an advanced multi-feature combined saliency detection model. Through qualitative and quantitative evaluation, our method consistently outperformed 4 global color (or intensity)-based saliency detection methods, resulting in higher precision.
机译:显着性检测是许多计算机视觉任务中的重要作用。我们提出了一种基于全局颜色和空间对比度的新型自下而上的对象级显着性检测方法。所提出的方法不仅考虑了图像的全球颜色对比度,还考虑了空间信息,导致高级多特征组合显着性检测模型。通过定性和定量评估,我们的方法始终如一地优于4个全局颜色(或强度)的显着性检测方法,从而提高精度。

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