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Video Saliency Detection Using Spatiotemporal Cues

Yu CHEN, Jing XIAO, Liuyi HU, Dan CHEN, Zhongyuan WANG, Dengshi LI

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Summary :

Saliency detection for videos has been paid great attention and extensively studied in recent years. However, various visual scene with complicated motions leads to noticeable background noise and non-uniformly highlighting the foreground objects. In this paper, we proposed a video saliency detection model using spatio-temporal cues. In spatial domain, the location of foreground region is utilized as spatial cue to constrain the accumulation of contrast for background regions. In temporal domain, the spatial distribution of motion-similar regions is adopted as temporal cue to further suppress the background noise. Moreover, a backward matching based temporal prediction method is developed to adjust the temporal saliency according to its corresponding prediction from the previous frame, thus enforcing the consistency along time axis. The performance evaluation on several popular benchmark data sets validates that our approach outperforms existing state-of-the-arts.

Publication
IEICE TRANSACTIONS on Information Vol.E101-D No.9 pp.2201-2208
Publication Date
2018/09/01
Publicized
2018/06/20
Online ISSN
1745-1361
DOI
10.1587/transinf.2017PCP0011
Type of Manuscript
Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
Category

Authors

Yu CHEN
  Wuhan University
Jing XIAO
  Wuhan University
Liuyi HU
  Wuhan University
Dan CHEN
  Wuhan University
Zhongyuan WANG
  Wuhan University
Dengshi LI
  Jianghan University

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