Bio-inspired visual saliency detection and its application on image retargeting

Authors:
Lijuan Duan;Chunpeng Wu;Haitao Qiao;Jili Gu;Jun Miao;Laiyun Qing;Zhen Yang
Affiliations:
College of Computer Science and Technology, Beijing University of Technology, Beijing, China;College of Computer Science and Technology, Beijing University of Technology, Beijing, China;College of Computer Science and Technology, Beijing University of Technology, Beijing, China;College of Computer Science and Technology, Beijing University of Technology, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;School of Information Science and Engineering, Graudate University of the Chinese Academy of Sciences, Beijing, China;College of Computer Science and Technology, Beijing University of Technology, Beijing, China
Venue:
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part I
Year:
2011

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Abstract

In this paper, we present a saliency guided image retargeting method. Our bio-inspired saliency measure integrates three factors: dissimilarity, spatial distance and central bias, and these three factors are supported by research on human vision system (HVS). To produce perceptual satisfactory retargeting images, we use the saliency map as the importance map in the retargeting method. We suppose that saliency maps can indicate informative regions, and filter out background in images. Experimental results demonstrate that our method outperforms previous retargeting method guided by the gray image on distorting dominant objects less. And further comparison between various saliency detection methods show that retargeting method using our saliency measure maintains more parts of foreground.