Global contrast based salient region detection

Ming Ming Cheng, Guo Xin Zhang, Niloy J. Mitra, Xiaolei Huang, Shi Min Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1554 Scopus citations

Abstract

Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their contents, and thus remains an important step in many computer vision tasks including image segmentation, object recognition, and adaptive compression. We propose a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence. The proposed algorithm is simple, efficient, and yields full resolution saliency maps. Our algorithm consistently outperformed existing saliency detection methods, yielding higher precision and better recall rates, when evaluated using one of the largest publicly available data sets. We also demonstrate how the extracted saliency map can be used to create high quality segmentation masks for subsequent image processing.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
PublisherIEEE Computer Society
Pages409-416
Number of pages8
ISBN (Print)9781457703942
DOIs
StatePublished - Jan 1 2011

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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    Cheng, M. M., Zhang, G. X., Mitra, N. J., Huang, X., & Hu, S. M. (2011). Global contrast based salient region detection. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 (pp. 409-416). [5995344] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR.2011.5995344