• DocumentCode
    694528
  • Title

    Video saliency detection using motion saliency filter

  • Author

    Lei Luo ; Rongxin Jiang ; Xiang Tian ; Yaowu Chen

  • Author_Institution
    Inst. of Adv. Digital Technol. & Instrum., Zhejiang Univ., Hangzhou, China
  • fYear
    2013
  • fDate
    12-13 Oct. 2013
  • Firstpage
    1045
  • Lastpage
    1049
  • Abstract
    In this paper, we propose a motion saliency filter to detect the salient regions in the video sequences. The motion vector field of each frame is first grouped into several elements with the aid of superpixel segmentation. Then, two measures are defined to rate the motion uniqueness and motion distribution of each element. The motion saliency of each element is derived as the fusion of the two measures. The final pixel-accurate saliency map is generated from a linear combination of the element motion saliency values. Moreover, the complete saliency computing process can be formulated with the N-D Gaussian filters which are with only linear computing complexity. Experimental results indicate that the proposed method could achieve better performance as compared to the state-of-the-art methods.
  • Keywords
    Gaussian processes; computational complexity; image motion analysis; image segmentation; image sequences; video signal processing; N-D Gaussian filters; complete saliency computing process; element motion saliency value; linear computing complexity; motion distribution; motion saliency filter; motion uniqueness; motion vector field; pixel-accurate saliency map; salient regions; superpixel segmentation; video saliency detection; video sequences; Filtering; Gaussian mixture model; Image color analysis; Motion measurement; Vectors; Video sequences; Visualization; Gaussian filtering; Saliency map; motion vector field; superpixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
  • Conference_Location
    Dalian
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2013.6967283
  • Filename
    6967283