Efficient Salient Region Detection with Soft Image Abstraction

Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel Crook; The IEEE International Conference on Computer Vision (ICCV), 2013, pp. 1529-1536

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.

Related Material


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[bibtex]
@InProceedings{Cheng_2013_ICCV,
author = {Cheng, Ming-Ming and Warrell, Jonathan and Lin, Wen-Yan and Zheng, Shuai and Vineet, Vibhav and Crook, Nigel},
title = {Efficient Salient Region Detection with Soft Image Abstraction},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {December},
year = {2013}
}