Efficient Salient Region Detection with Soft Image Abstraction


Ming-Ming Cheng
      Jonathan Warrell       Wen-Yan Lin        Shuai Zheng       Vibhav Vineet         Nigel Crook

Vision Group, Oxford Brookes University

Abstract

Detecting visually salient regions in images is one of the fundamental problems in computer vision. We propose a novel method to decompose an image into large scale perceptually homogeneous elements for efficient salient region detection, using a soft image abstraction representation. By considering both appearance similarity and spatial distribution of image pixels, the proposed representation abstracts out unnecessary image details, allowing the assignment of comparable saliency values across similar regions, and producing perceptually accurate salient region detection. We evaluate our salient region detection approach on the largest publicly available dataset with pixel accurate annotations. The experimental results show that the proposed method outperforms 18 alternate methods, reducing the mean absolute error by 25.2% compared to the previous best result, while being computationally more efficient.

Paper

  1. Efficient Salient Region Detection with Soft Image Abstraction. Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel Crook. ICCV 2013. [pdf][bib][latex]

Supplemental materials

  • Results comparisons to 18 alternative methods for MSRA 1000 dataset in a 79M PDF.
  • Our result saliency maps: 31MB ZIP, results for other methods (360M ZIP).
  • Prototype software: 2M ZIP.
  • C++ source code is available. It runs 90 fps at my computer (CPU: Intel(R) core (TM) i7 cup 970 @ 3.2 GHz).

Other closely related projects:

1. Salient object detection and segmentation

2. Group saliency

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29 Comments on "Efficient Salient Region Detection with Soft Image Abstraction"

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LingLingCui
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LingLingCui

程老师,我想问一下《Efficient Salient Region Detection with Soft Image Abstraction》这篇paper的程序包解压时的解压密码??谢谢!

Fan
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Fan

程老师,您好,我运行了你的文章《Efficient Salient Region Detection with Soft Image Abstraction》提供的代码,运行环境vs2010,win7 64位系统,我用你提供的代码聚类,相同的图,你文章中是3类,我聚出来是6类,不知道为什么。还望您解答,谢谢。

LingLingCui
Guest
LingLingCui

你好,这篇文章附带的程序,解压的时候有解压密码,你可以提供一下吗?

hengliang
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hengliang

程老师,提供的代码好像存在bug,在函数void CmSaliencyGC::MergeGMMs()里,如果_NUM = 1,那么语句int i1 = pIdx[0].second, i2 = pIdx[1].second;就会访问越界,是不是用GMM分解图像的时候,得到的elements应该大于1个(估计),如数据集SED2里的图片b17leon000.jpg就会出现上述错误;又试了提供的software没有报错。期待您的答疑,谢谢。

Nicholas
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Nicholas

我也是碰到同样的问题 求解答

xingxing
Guest
xingxing

你好,麻烦问一下,你运行程老师的GMM合并的代码能得到预期的结果么?我运行的时候得不到聚类结果

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