Intra-Saliency Transfer for Effective Salient Object Detection

Aditya Kompella, R. Kulkarni
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引用次数: 2

Abstract

A new color contrast based, bottom up saliency method called INS has been proposed in this paper. Intra-saliency transfer and multiple distance functions have been exploited effectively in the INS method. A color-based super-pixel segmentation approach has been used in the INS method in order to decompose the image into regions. Further, three distance functions are used to measure the saliency to effectively characterize the salient regions. These functions are evaluated and integrated to effectively determine the final saliency map. The INS method has been evaluated exhaustively on the MSRA-1000 benchmark image dataset available in public domain. Further, the results of the INS method have been compared with those of twelve state-of-the-art salient object detection methods found in recent literature. The INS method has exhibited superior saliency detection performance compared to the methods used for comparison.
有效显著性目标检测的显著性内迁移
本文提出了一种新的基于颜色对比度的自底向上显著性方法INS。该方法有效地利用了显著性内转移和多距离函数。INS方法采用了基于颜色的超像素分割方法,将图像分解为多个区域。此外,使用三个距离函数来测量显著性,以有效地表征显著区域。对这些函数进行评估和整合,以有效地确定最终的显著性图。INS方法已经在公共领域可用的MSRA-1000基准图像数据集上进行了详尽的评估。此外,将INS方法的结果与最近文献中发现的12种最先进的显著目标检测方法进行了比较。与用于比较的方法相比,INS方法表现出优越的显著性检测性能。
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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