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Video Saliency Detection Using Spatiotemporal Cues
Yu CHEN Jing XIAO Liuyi HU Dan CHEN Zhongyuan WANG Dengshi LI
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2018/09/01
Online ISSN: 1745-1361
Type of Manuscript: Special Section PAPER (Special Section on Picture Coding and Image Media Processing)
saliency detection, spatio-temproal cues, foreground prior, spatial distribution, background noise suppression,
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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.