期刊文献+

背景感知的显著性检测算法 被引量:5

Background aware saliency detection
下载PDF
导出
摘要 显著性检测算法能够提取场景中的重要目标,因而在图像和视频处理领域有着重要应用。但目前的显著性检测算法几乎都以目标与背景之间存在显著差异为前提,利用目标与背景的差异以及目标本身的空间相关性进行算法的设计。本文则从图像的背景信息出发,首先利用超像素算法对图像进行预分割,去除图像中不必要的细节信息;然后利用背景信息获得初步的显著性检测结果;最后将多尺度显著性检测结果进行融合,得到最终的显著性图。实验结果表明,本文算法的性能远优于现有检测算法。 Saliency detection can abstract important targets,so it has important application in the field of image and video processing.But almost all the current saliency detection algorithms are based on significant con-trast between the target and the background,and they compute saliency with differences between targets and backgrounds,and space correlation within targets.A new method is provided using the background infonma-tion.First,an image is decomposed into compact elements that abandon unnecessary details.Then the initial saliency map is computed with background information.Finally the multi-scale information is fused to promote the detection performance.A detailed experimental evaluation shows that the proposed method outperforms all state-of-the-art approaches.
出处 《系统工程与电子技术》 EI CSCD 北大核心 2014年第8期1668-1672,共5页 Systems Engineering and Electronics
基金 中央高校基本科研业务费(K5051202004)资助课题
关键词 显著性检测 背景信息 边缘 多尺度融合 saliency detection background information edge multi-scale fusion
  • 相关文献

参考文献15

  • 1Borji A,Itti L. State of-the-art in visual attention modeling[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2013,35(1): 185-207.
  • 2Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1998, 20(11) : 1254 - 1259.
  • 3Ma Y F, Zhang H J. Contrast based image attention analysis by using fuzzy growing[C]// Proc. of the ACM Multimedia, 2003 : 374 - 381.
  • 4Hou X, Zbang L. Saliency detection: a spectral residual ap- proach[C] ff Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2007 : 1 - 8.
  • 5Hou X, Harel J, Koch C. Image signature: highlighting sparse salient regions[J]. IEEE Trans. on Pattern Analysis and Ma- chine Intelligence, 2012, 34(1) : 194 - 201.
  • 6Achanta R, Hemami S, Estrada F, et al. Frequency tuned sali- ent region detection [C] //Proc. of the IEEE Conference onComputer Vision and Pattern Recognition, 2009 : 1597 - 1604.
  • 7Goferman S, Zelnik M L, Tal A. Context-aware saliency detec- tion[J]. IEEE Trans. on Pattern Analysis and Machine Intelli- gence, 2012, 34(10): 1915-1926.
  • 8Cheng M M, Zhang G X, Mitra N J, et al. Global contrast based sa- lient region detection[C]//Proc, of the IEEE Conference on Com- puter Vision and Pattern Recognition, 2011:409 - 416.
  • 9黄志勇,何发智,蔡贤涛,周正钦,刘静,梁铭铭,陈晓.一种随机的视觉显著性检测算法[J].中国科学:信息科学,2011,41(7):863-874. 被引量:15
  • 10胡正平,孟鹏权.全局孤立性和局部同质性图表示的随机游走显著目标检测算法[J].自动化学报,2011,37(10):1279-1284. 被引量:11

二级参考文献46

  • 1Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.
  • 2Walther D, Koch C. Modeling attention to salient proto-objects. Neural Networks, 2006, 19(9): 1395-1407.
  • 3Li Q, Wang S Z, Zhang X P. Hierarchical identification of visually salient image regions. In: Proceedings of the International Conference on Audio, Language and Image Processing. Shanghai, China: IEEE, 2008. 1708-1712.
  • 4Hou X D, Zhang L Q. Saliency detection: a spectral residual approach. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Minneapolis, USA: IEEE, 2007. 1-8.
  • 5Guo C L, Ma Q, Zhang L M. Spatio-temporal saliency detection using phase spectrum of quaternion Fourier transform. In: Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, USA: IEEE, 2008. 1-8.
  • 6Guo C L, Zhang L M. A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Transactions on Image Processing, 2010, 19(1): 185-198.
  • 7Gopalakrishnan V, Hu Y Q, Rajan D. Salient region detection by modeling distributions of color and orientation. IEEE Transactions on Multimedia, 2009, 11(5): 892-905.
  • 8Zhang W, Wu Q M J, Wang G H, Yin H B. An adaptive computational model for salient object detection. IEEE Transactions on Multimedia, 2010, 12(4): 300-316.
  • 9Harel J, Koch C, Perona P. Graph-based visual saliency. In: Proceedings of the Neural Information Processing Systems. Vancouver, Canada: The MIT Press, 2006. 545-552.
  • 10Gopalakrishnan V, Hu Y Q, Rajan D. Random walks on graphs to model saliency in images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE, 2009. 1698-1705.

共引文献44

同被引文献42

  • 1田媚.模拟自顶向下视觉注意机制的感知模型研究[D].北京:北京交通大学,2007.
  • 2Itti L, Kouch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259.[DOI:10.1109/34.730558].
  • 3Ma Y F, Zhang H J. Contrast-based image attention analysis by using fuzzy growing[C]//Proceedings of the 11th ACM International Conference on Multimedia. New York: Association for Computing Machinery, 2003 : 374-381. [DOI:10.1145/957013.957094].
  • 4Rahtu E, Kannala J, Salo M, et al. Segmenting salient objects from images and videos[C]//Proceedings of the 11th European Conference on Computer Vision. Heraklion, Greece: Springer, 2010: 366-379. [DOI: 10.1007/978-3-642-15555-0_27].
  • 5Achanta R, Hemami S, Estrada F, et al. Frequency-tuned salient region detection[C]/Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition. Miami, USA: IEEE Press, 2009: 1597-1604. [DOI: 10.1109/CVPRW.2009.5206596].
  • 6Cheng M M, Zhang G X, Mitra N J. et al. Global Contrast based Salient Region Detection[C]/Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence: IEEE, 2011: 409-416. [DOI: 10.1109/CVPR.2011.5995344].
  • 7Perazzi F, Kr?ahenb?uhl P, Pritch Y, et al. Saliency filters: contrast based filtering for salient region detection[C]//Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition. Providence, USA: IEEE, 2012: 733-740. [DOI: 10.1109/CVPR.2012.6247743].
  • 8Bruce N, Tsotosos J. Saliency based on information maximization[C]//Proceedings of Advances in Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2005: 155-162. [DOI: 10.1007/978-3-642-33786-4_24].
  • 9Bruce N, Tsotsos J. Saliency, attention, and visual search: an information theoretic approach[J]. Journal of Vision. 2009, 9(3): 1-24. [DOI: 10.1167/9.3.5].
  • 10Guo C, Ma Q, Zhang L. Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Minneapoils, USA: IEEE, 2008: 2908-2915.[DOI: 10.1109/CVPR.2008.4587715].

引证文献5

二级引证文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部