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Content Provider | IEEE Xplore Digital Library |
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Author | Ming-Ming Cheng Warrell, J. Wen-Yan Lin Shuai Zheng Vineet, V. Crook, N. |
Copyright Year | 2013 |
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. |
Sponsorship | IEEE Comput. Soc. |
Starting Page | 1529 |
Ending Page | 1536 |
File Size | 1560988 |
Page Count | 8 |
File Format | |
ISBN | 9781479928408 |
ISSN | 15505499 |
DOI | 10.1109/ICCV.2013.193 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-12-01 |
Publisher Place | Australia |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image color analysis Visualization Abstracts Correlation Histograms Estimation Graphical models object of interest segmentation salient object detection visual attention image abstraction |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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