Detection of salient objects in computer synthesized images based on object-level contrast

L. Dong, Weisi Lin, Yuming Fang, Shiqian Wu, S. H. Soon
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引用次数: 0

Abstract

In this work, we propose a method to detect visually salient objects in computer synthesized images from 3D meshes. Different from existing detection methods on graphic saliency which compute saliency based on pixel-level contrast, the proposed method computes saliency by measuring object-level contrast of each object to the other objects in a rendered image. Given a synthesized image, the proposed method first extracts dominant colors from each object, and represents each object with the dominant color descriptor (DCD). Saliency is measured as the contrast between the DCD of the object and the DCDs of its surrounding objects. We evaluate the proposed method on a data set of computer rendered images, and the results show that the proposed method obtains much better performance compared with existing related methods.
基于目标级对比度的计算机合成图像中显著目标的检测
在这项工作中,我们提出了一种从3D网格中检测计算机合成图像中视觉显著目标的方法。与现有图形显著性检测方法基于像素级对比度计算显著性不同,该方法通过测量渲染图像中每个对象与其他对象的对象级对比度来计算显著性。该方法首先从合成图像中提取各目标的主色,并用主色描述符(DCD)表示每个目标。显著性是用物体的DCD与其周围物体的DCD之间的对比度来衡量的。在计算机渲染图像数据集上对所提方法进行了评价,结果表明所提方法比现有的相关方法获得了更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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