期刊文献+

基于区域协方差的视频显著度局部空时优化模型 被引量:3

A Local Spatiotemporal Optimization Framework for Video Saliency Detection Using Region Covariance
下载PDF
导出
摘要 显著度检测在计算机视觉中应用非常广泛,图像级的显著度检测研究已较为成熟,但视频显著度因其高度挑战性研究相对较少。该文借鉴图像级显著度算法的思想,提出一种通用的空时特征提取与优化模型来检测视频显著度。首先利用区域协方差矩阵构造视频的空时特征描述子,然后计算对比度得出初始显著图,最后通过联合前后帧的局部空时优化模型得到最终的显著图。在2个公开视频显著性数据集上的实验结果表明,所提算法性能优于目前的主流算法,同时具有良好的扩展性。 Visual saliency is widely applied to computer vision. Image saliency detection has been extensively studied, while there are only a few effective methods of computing saliency for videos owing to its high challenge. Inspired by image saliency methods, this paper proposes a unified spatiotemporal feature extraction and optimization framework for video saliency. First, the spatiotemporal feature descriptor is constructed via region covariance. Then, initial saliency map is computed by the local contrast of the descriptor. Finally, a local spatiotemporal optimization framework considering the previous and next frames of the current one is modeled to obtain the final saliency map. Extensive experiments on two public datasets demonstrate that the proposed algorithm not only outperforms the state-of-the-art methods, but also is of great extendibility.
出处 《电子与信息学报》 EI CSCD 北大核心 2016年第7期1586-1593,共8页 Journal of Electronics & Information Technology
基金 国家自然科学基金青年基金(61501509)~~
关键词 视频显著度 区域协方差 局部对比度 局部空时优化 Video saliency Region covariance Local contrast Local spatiotemporal optimization
  • 相关文献

参考文献32

  • 1BORJI A, CHENG M, JIANG H, et al. Salient object detection: A survey[OL]. http://arxiv.org/abs/1411.5878, 2014. 被引量:1
  • 2BORJI A, CHENG M, JIANG H, et al. Salient object detection: A benchmark[J]. IEEE Transactions on Image Processing, 2015, 24(12): 5706-5722. 被引量:1
  • 3ROTHER C, KOLMOGOROV V, and BLAKE A. Grabcut: Interactive foreground extraction using iterated graph cuts[J]. ACM Transactions on Graphics, 2004, 23(1): 309-314. 被引量:1
  • 4DING Y, XIAO J, and YU J. Importance filtering for image retargeting[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, 2011: 89-96. 被引量:1
  • 5MAHADEVAN V and VASOONCEIOS N. Saliency-based discriminant tracking[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, USA, 2009: 1007-1013. 被引量:1
  • 6SHARMA G, JURIE F, and SCHMID C. Discriminative spatial saliency for image classification[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Rhode Island, USA, 2012: 3506-3513. 被引量:1
  • 7HADIZADEH H and BAJIC I. Saliency-aware video compression[J]. IEEE Transactions on Image Processing, 2014, 23(1): 19-33. 被引量:1
  • 8CHENG M, ZHANG G, MIERA N, et al. Global contrast based salient region detection[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, 2011: 409-416. 被引量:1
  • 9PERAZZI F, KRAHENBUHL P, PRITCH Y, et al. Saliency filters: Contrast based filtering for salient region detection[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Rhode Island, USA, 2012: 733-740. 被引量:1
  • 10YANG C, ZHANG L, LU H, et al. Saliency detection via graph-based manifold ranking[C]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, USA, 2013: 3166-3173. 被引量:1

二级参考文献39

  • 1Itti L, Koch C, and 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. 被引量:1
  • 2Achanta R, Estrada F, Wils P, et al.. Salient region detection and segmentation[C]. Proceedings of the 6th International Conference on Computer Vision Systems, Santorini, Greece, 2008: 66-75. 被引量:1
  • 3Hou X and Zhang L. Saliency detection: a spectral residual approach[C]. IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, Minnesota, USA, 2007: 1-8. 被引量:1
  • 4Kim C, Kim J, and Sim J. Multiscale saliency detection using random walk with restart[J]. IEEE Transactions on Circuits and Systems ]or Video Technology, 2014, 24(2): 198-210. 被引量:1
  • 5Perazzi F, Krahenbuhl P, Pritch Y, et al.. Saliency filters: contrast based filtering for salient region detection[C]. Proceeding of IEEE International Conferrence of Computer Vision and Pattern Recognition, RI, USA, 2012: 733-740. 被引量:1
  • 6Wei Yi-chen, Wen Fang, and Zhu Wang-jiang. Geodesic saliency using back ground priors[C]. Proceeding of the European Conference on Computer Vision 2012: Part III, Florence, Italy, 2012: 29-42. 被引量:1
  • 7Veksler O, Boykov Y, and Mehrani P. Superpixels andsupervoxels in an energy optimization framework[C]. Proceeding of the European Conference on Computer Vision 2010, Berlin Heidelberg 2010: 211-224. 被引量:1
  • 8Achanta R, Hemami S, Estrada F, et al.. Frequency-tuned salient region detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA, 2009: 1597-1604. 被引量:1
  • 9Cheng M, Zhang G, Mitra N, et al.. Global contrast based salient region detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, Colorado Springs, USA, 2011: 409-416. 被引量:1
  • 10Zhai Y and Shah M. Visual attention detection in video sequences using spatiotemporal cues[C]. Proceedings of ACM Multimedia, Santa Barbara, CA, USA, 2006: 815-824. 被引量:1

共引文献26

同被引文献8

引证文献3

二级引证文献10

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