@inbook {IOPORT.05985004,
    author       = {Duan, Lijuan and Wu, Chunpeng and Qiao, Haitao and Gu, Jili and Miao, Jun and Qing, Laiyun and Yang, Zhen},
    title        = {Bio-inspired visual saliency detection and its application on image retargeting.},
    year         = {2011},
    booktitle    = {Neural information processing. 18th international conference, ICONIP 2011, Shanghai, China, November 13--17, 2011. Proceedings, Part I},
    isbn         = {978-3-642-24954-9},
    pages        = {182-189},
    publisher    = {Berlin: Springer},
    doi          = {10.1007/978-3-642-24955-6_22},
    abstract     = {Summary: 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.},
    identifier   = {05985004},
}